Hand tracking stabilization

Abstract

An augmented reality (AR) system (352) provides stabilization of hand tracking input data. The AR system enables display of a user interface of an AR application (328). The AR system uses one or more camera devices (326) of the AR system to capture video frame tracking data of gestures being made by the user while the user (332) interacts with the AR user interface. The AR system generates skeletal 3D model data of the user's hand based on the video frame tracking data, the skeletal 3D model data including one or more skeletal 3D model features corresponding to the identified visual landmarks of the portions of the user's hand. The AR system generates target data based on the skeletal 3D model data, wherein the target data identifies a virtual 3D object of the AR user interface. The AR system filters the target data using a target filter component and provides the filtered target data to the AR application.

Description

[0001] Priority Claim

[0002] This application claims the benefit of priority to U.S. application serial number 17 / 822,634, filed on August 26, 2022, the entire contents of which are incorporated herein by reference. Technical Field

[0003] The present disclosure relates generally to user interfaces and, more particularly, to user interfaces for augmented reality or virtual reality. Background Art

[0004] The head wearable device can be implemented with a transparent display or a semi-transparent display, through which the user of the head wearable device can view the surrounding environment. Such a head wearable device enables the user to view the surrounding environment through the transparent display or the semi-transparent display, and can also see objects (e.g., virtual objects, such as renderings of 2D or 3D graphic models, images, videos, text, etc.) generated for display as part of the surrounding environment and / or superimposed on the surrounding environment. This is generally referred to as "augmented reality" or "AR". The head wearable device can also completely block the user's field of view and display a virtual environment through which the user can move or be moved. This is generally referred to as "virtual reality" or "VR". In a hybrid form, a view of the surrounding environment is captured using a camera device, and then the view is displayed to the user on a display that blocks the user's eyes together with the augmentation. As used herein, unless the context indicates otherwise, the term AR refers to augmented reality, virtual reality, and any mixture of these technologies.

[0005] Users of head wearable devices can access and use computer software applications to perform various tasks or participate in entertainment activities. In order to use the computer software application, the user interacts with a user interface provided by the head wearable device. BRIEF DESCRIPTION OF THE DRAWINGS

[0006] In the accompanying drawings (which are not necessarily drawn to scale), similar reference numerals may describe similar components in different views. To easily identify the discussion of any particular element or action, the highest digit or digits in the reference numeral refer to the figure number in which the element is first introduced. Some non-limiting examples are shown in the figures of the accompanying drawings, in which:

[0007] Figure 1A is a stereoscopic diagram of a head mounted device according to some examples.

[0008] Figure 1B According to some examples Figure 1A Additional views of the head-mounted device.

[0009] Figure 2 is a diagrammatic representation of a machine in the form of a computer system according to some examples within which a set of instructions may be executed for causing the machine to perform any one or more of the methodologies discussed herein.

[0010] Figure 3A and Figure 3B is an illustration of an AR user interface according to some examples.

[0011] Figure 3C is a collaboration diagram of components of an AR system that provides an AR user interface according to some examples.

[0012] Figure 3D is an activity diagram of a gesture and hand pose detection method used by an AR system to provide user input to an AR user interface in accordance with some implementations.

[0013] Figure 4 is a diagrammatic representation of a networked environment in which the present disclosure may be deployed, according to some examples.

[0014] Figure 5 A system of head wearable devices according to some examples.

[0015] Figure 6 is a diagrammatic representation of data structures as maintained in a database according to some examples.

[0016] Figure 7 is a diagrammatic representation of a messaging system having both client-side and server-side functionality according to some examples.

[0017] Figure 8 is a block diagram illustrating a software architecture within which examples may be implemented.

[0018] Other technical features may be readily apparent to those skilled in the art from the accompanying drawings, descriptions and claims. DETAILED DESCRIPTION

[0019] The AR application provided by the head wearable device provides an interaction to the user, wherein a target component is used to select an interaction with a target virtual 3D object of an AR user interface of the AR application, and an actuation component is used to initiate an interaction with the virtual 3D object. For example, some hand interaction frameworks use a combination of a hand gesture for selecting a target virtual 3D object and a "pinch" gesture for actuating an interaction with the target virtual 3D object. Because the pinch gesture can change the hand gesture, the pinch gesture may interfere with the selection of the intended target virtual 3D object for the interaction.

[0020] In some examples, computer vision pose and hand pose estimation is improved by training an ML hand tracking model so that some recognized hand poses are not affected by hand movement during a pinch gesture. In some examples, this is done by annotating training hand video frame tracking data to ignore some features of a user's hand, and training the ML hand tracking model using the specially annotated training hand video frame tracking data. In some examples, the hand video frame tracking data is selected to include video frame tracking data in which knuckle features do not move during a pinch gesture.

[0021] In some examples, the hand tracking pipeline temporally smoothes or filters one or more skeletal 3D model features of the skeletal 3D model corresponding to the user's hand. In some examples, the degree of temporal smoothing or filtering is applied differently to the skeletal 3D model features, such that a greater degree of smoothing or filtering is applied to a particular skeletal 3D model feature than to the degree of smoothing or filtering applied to the rest of the skeletal 3D model features.

[0022] In some examples, temporal smoothing or filtering applied to features of the skeletal 3D model is dynamically adjusted so that the degree of smoothing applied to the target virtual 3D object is adjusted in proportion to the probability that a particular posture or hand pose is beginning.

[0023] In some examples, the hand tracking pipeline employs composite hand features to determine a pose or hand posture. Multiple hand, wrist, and shoulder features are synthesized into features that minimize changes in the target during a pose.

[0024] In some examples, when changing from one target virtual 3D object to another virtual 3D object, the previous state of the user's hand when the user's hand was hovering over or targeting the virtual 3D object for interaction is taken into account. In an example, in a distance-based selection algorithm, the virtual 3D object closest to the center of the user's hand is selected, and then a term of a hysteresis function or debounce provides a reward to the currently selected virtual 3D object, such as by reducing the calculated distance.

[0025] Figure 1A is a perspective view of a head wearable device 100 according to some examples. The head wearable device 100 may be an AR system such as Figure 4The head wearable device 100 may include a frame 102 made of any suitable material, such as plastic or metal including any suitable shape memory alloy. In one or more examples, the frame 102 includes a first or left optical element holder 104 (e.g., a display or lens holder) and a second or right optical element holder 106 connected by a nose bridge 112. A first or left optical element 108 and a second or right optical element 110 may be disposed in the left optical element holder 104 and the right optical element holder 106, respectively. The right optical element 110 and the left optical element 108 may be lenses, displays, display components, or combinations of the foregoing. Any suitable display component may be disposed in the head wearable device 100.

[0026] The frame 102 additionally includes a left arm or temple piece 122 and a right arm or temple piece 124. In some examples, the frame 102 can be formed from a single piece of material to have a unitary or unitary construction.

[0027] The head wearable device 100 may include a computing device, such as a computer 120, which may be of any suitable type so as to be carried by the frame 102, and in one or more examples, may be of a suitable size and shape so as to be partially disposed in one of the left temple piece 122 or the right temple piece 124. The computer 120 may include one or more processors with memory, wireless communication circuitry, and a power source. As discussed below, the computer 120 includes a low-power circuitry, a high-speed circuitry, and a display processor. Various other examples may include these elements in different configurations or integrated together in different ways. Additional details of various aspects of the computer 120 may be implemented as shown in the machine 200 discussed below.

[0028] The computer 120 additionally includes a battery 118 or other suitable portable power supply. In some examples, the battery 118 is disposed in the left temple piece 122 and is electrically coupled to the computer 120 disposed in the right temple piece 124. The head wearable device 100 may include a connector or port (not shown) suitable for charging the battery 118, a wireless receiver, transmitter or transceiver (not shown), or a combination of such devices.

[0029] The head wearable device 100 includes a first camera or left camera 114 and a second camera or right camera 116. Although two cameras are depicted, other examples contemplate the use of a single or additional (i.e., more than two) cameras. In some examples, the head wearable device 100 includes one or more visible light cameras, an infrared emitter, and an infrared camera. In one or more examples, in addition to the left camera 114 and the right camera 116, the head wearable device 100 also includes any number of input sensors or other input / output devices. Such sensors or input / output devices may additionally include biometric sensors, positioning sensors, motion sensors, etc.

[0030] In some examples, left camera 114 and right camera 116 provide video frame tracking data for use by head wearable device 100 to extract 3D information from the real-world scene.

[0031] The head wearable device 100 may also include a touchpad 126 mounted to or integrated with one or both of the left temple piece 122 and the right temple piece 124. The touchpad 126 is typically arranged vertically, approximately parallel to the temple of the user in some examples. As used herein, typically vertically aligned means that the touchpad is more vertical than horizontal, but may be more vertical than this. Additional user input can be provided by one or more buttons 128, which in the example shown are disposed on the outer upper edges of the left optical element holder 104 and the right optical element holder 106. The one or more touchpads 126 and buttons 128 provide a means by which the head wearable device 100 can receive input from a user of the head wearable device 100.

[0032] Figure 1B The head wearable device 100 is shown from the perspective of a user wearing the head wearable device 100. For clarity, the Figure 1A Many of the components shown in FIG. Figure 1A As stated, Figure 1B The head wearable device 100 shown includes a left optical element 140 and a right optical element 144, which are fixed in a left optical element holder 132 and a right optical element holder 136, respectively.

[0033] The head wearable device 100 includes: a right front optical component 130, the right front optical component 130 includes a left near-eye display 150 and a right near-eye display 134; and a left front optical component 142, the left front optical component 142 includes a left projector 146 and a right projector 152.

[0034] In some examples, the near-eye display is a waveguide. The waveguide includes a reflective or diffractive structure (e.g., a grating and / or an optical element, such as a mirror, lens, or prism). Light 138 emitted by the right projector 152 encounters the diffractive structure of the waveguide of the right near-eye display 134, which guides the light toward the right eye of the user to provide an image on or in the right optical element 144, which is superimposed on the view of the real-world scene seen by the user. Similarly, light 148 emitted by the left projector 146 encounters the diffractive structure of the waveguide of the left near-eye display 150, which guides the light toward the left eye of the user to provide an image on or in the left optical element 140, which is superimposed on the view of the real-world scene seen by the user. The combination of the GPU, the right front optical assembly 130, the left optical element 140, and the right optical element 144 provides the optical engine of the head wearable device 100. The head wearable device 100 uses an optical engine to generate an overlay of the user's view of a real-world scene, including displaying a user interface to the user of the head wearable device 100.

[0035] However, it should be understood that other display technologies or configurations may be utilized within the optical engine to display images to the user in the user's field of view. For example, instead of the hand tracking pipeline 348 and waveguide, an LCD, LED, or other display panel or surface may be provided.

[0036] In use, the user of the head wearable device 100 will see information, content, and various user interfaces on the near-eye display. As described in more detail herein, the user can then use the touch pad 126 and / or buttons 128, on an associated device (e.g., Figure 5 The device 100 may be used to interact with the head wearable device 100 through touch input or voice input on a mobile device 414 shown in FIG. 1 , and / or hand movements, positioning, and location recognized by the head wearable device 100.

[0037] In some examples, head wearable device 100 includes an AR system. In some examples, head wearable device 100 is a component of an AR system that includes additional computing components. In some examples, head wearable device 100 is a component of an AR system that includes additional user input systems or devices.

[0038] Machine Architecture

[0039] Figure 2200 within which instructions 202 (e.g., software, programs, applications, applet, app, or other executable code) may be executed for causing the machine 200 to perform any one or more of the methods discussed herein. For example, the instructions 202 may cause the machine 200 to perform any one or more of the methods described herein. The instructions 202 convert a general purpose, unprogrammed machine 200 into a specific machine 200 that is programmed to perform the functions described and illustrated in the manner described. The machine 200 may operate as a standalone device or may be coupled (e.g., networked) to other machines. In a networked deployment, the machine 200 may operate in the capacity of a server machine or a client machine in a server-client network environment or as a peer machine in a peer-to-peer (or distributed) network environment. The machine 200 may include, but is not limited to, a server computer, a client computer, a personal computer (PC), a tablet computer, a laptop computer, a netbook, a set-top box (STB), a personal digital assistant (PDA), an entertainment media system, a cellular phone, a smart phone, a mobile device, a wearable device (e.g., a smart watch), a smart home device (e.g., a smart appliance), other smart devices, a web device, a network router, a network switch, a network bridge, or any machine capable of sequentially or otherwise executing instructions 202 specifying actions to be taken by the machine 200. In addition, although a single machine 200 is shown, the term "machine" should also be taken to include a collection of machines that individually or jointly execute instructions 202 to perform any one or more of the methods discussed herein. For example, the machine 200 may include a computing system 402 or any of a plurality of server devices forming part of an interactive server system 410. In some examples, the machine 200 may also include both a client system and a server system, wherein certain operations of a particular method or algorithm are performed on the server side and certain operations of a particular method or algorithm are performed on the client side.

[0040] The machine 200 may include a processor 204, a memory 206, and an input / output (I / O) component 208 that may be configured to communicate with each other via a bus 210. In an example, the processor 204 (e.g., a central processing unit (CPU), a reduced instruction set computing (RISC) processor, a complex instruction set computing (CISC) processor, a graphics processing unit (GPU), a digital signal processor (DSP), an application specific integrated circuit (ASIC), a radio frequency integrated circuit (RFIC), another processor, or any suitable combination thereof) may include, for example, a processor 212 and a processor 214 that execute instructions 202. The term "processor" is intended to include multi-core processors, which may include two or more independent processors (sometimes referred to as "cores") that may execute instructions simultaneously. Although Figure 2 Multiple processors 204 are shown, but the machine 200 may include a single processor with a single core, a single processor with multiple cores (e.g., a multi-core processor), multiple processors with a single core, multiple processors with multiple cores, or any combination thereof.

[0041] The memory 206 includes a main memory 216, a static memory 240, and a storage unit 218, which are all accessible by the processor 204 via the bus 210. The main memory 206, the static memory 240, and the storage unit 218 store instructions 202 that embody any one or more of the methodologies or functions described herein. The instructions 202 may also reside, completely or partially, within the main memory 216, within the static memory 240, within the machine-readable medium 220 within the storage unit 218, within at least one of the processors 204 (e.g., within a cache memory of a processor), or within any suitable combination thereof during execution thereof by the machine 200.

[0042] The I / O components 208 may include various components for receiving input, providing output, generating output, sending information, exchanging information, capturing measurements, etc. The specific I / O components 208 included in a particular machine will depend on the type of machine. For example, a portable machine such as a mobile phone may include a touch input device or other such input mechanism, while a headless server machine may not include such a touch input device. It should be understood that the I / O components 208 may include Figure 2 , many other components not shown in the figure. In various examples, the I / O component 208 may include a user output component 222 and a user input component 224. The user output component 222 may include a visual component (e.g., a display such as a plasma display panel (PDP), a light emitting diode (LED) display, a liquid crystal display (LCD), a projector, or a cathode ray tube (CRT)), an acoustic component (e.g., a speaker), a tactile component (e.g., a vibration motor, a resistance mechanism), other signal generators, etc. The user input component 224 may include an alphanumeric input component (e.g., a keyboard, a touch screen configured to receive alphanumeric input, an optical keyboard, or other alphanumeric input component), a point-based input component (e.g., a mouse, a touch pad, a trackball, a joystick, a motion sensor, or other pointing instrument), a tactile input component (e.g., a physical button, a touch screen or other tactile input component that provides location and force of a touch or touch gesture), an audio input component (e.g., a microphone), etc.

[0043] In another example, the I / O component 208 may include a biometric component 226, a motion component 228, an environment component 230, or a position component 232, as well as various other components. For example, the biometric component 226 includes components for detecting expressions (e.g., hand expressions, facial expressions, voice expressions, body postures, or eye tracking), measuring biosignals (e.g., blood pressure, heart rate, body temperature, sweating, or brain waves), identifying people (e.g., voice recognition, retinal recognition, facial recognition, fingerprint recognition, or EEG-based recognition), etc. The motion component 228 includes: an acceleration sensor component (e.g., an accelerometer), a gravity sensor component, and a rotation sensor component (e.g., a gyroscope).

[0044] The environmental components 230 include, for example, one or more cameras (with still image / photo and video capabilities), an illumination sensor component (e.g., a photometer), a temperature sensor component (e.g., one or more thermometers that detect ambient temperature), a humidity sensor component, a pressure sensor component (e.g., a barometer), an acoustic sensor component (e.g., one or more microphones that detect background noise), a proximity sensor component (e.g., an infrared sensor that detects nearby objects), a gas sensor (e.g., a gas detection sensor for detecting concentrations of hazardous gases for safety purposes or for measuring pollutants in the atmosphere), a depth or distance sensor (e.g., a sensor for determining the distance to an object or for determining the depth of an object feature in a 3D coordinate system), or other components that can provide indications, measurements, or signals corresponding to the surrounding physical environment.

[0045] With respect to cameras, computing system 402 may have a camera system including, for example, a front-facing camera on a front surface of computing system 402 and a rear-facing camera on a rear surface of computing system 402. The front-facing camera may, for example, be used to capture still images and videos of a user of computing system 402 (e.g., “selfies”), which may then be enhanced with the enhancement data (e.g., filters) described above. The rear-facing camera may, for example, be used to capture still images and videos in a more conventional camera mode, where the images are similarly enhanced with the enhancement data. In addition to the front-facing camera and the rear-facing camera, computing system 402 may also include a 360° camera for capturing 360° photos and videos.

[0046] Additionally, the camera system of computing system 402 may include dual rear cameras (e.g., a main camera and a depth sensing camera), or even triple, quad, or quintuple rear camera configurations on the front and back sides of computing system 402. For example, these multiple camera systems may include a wide-angle camera, an ultra-wide-angle camera, a telephoto camera, a macro camera, and a depth sensor.

[0047] The location component 232 includes a positioning sensor component (e.g., a GPS receiver component), an altitude sensor component (e.g., an altimeter or barometer that detects air pressure, from which the altitude can be obtained), an orientation sensor component (e.g., a magnetometer), and the like.

[0048] A variety of technologies can be used to achieve communication. The I / O component 208 also includes a communication component 234 that is operable to couple the machine 200 to a network 236 or a device 238 via a corresponding coupling or connection. For example, the communication component 234 may include a network interface component or other suitable device that interfaces with the network 236. In other examples, the communication component 234 may include a wired communication component, a wireless communication component, a cellular communication component, a near field communication (NFC) component, Parts (e.g. Low power consumption), Components and other communication components for providing communication via other modalities. Device 238 can be another machine or any peripheral device among a variety of peripheral devices (e.g., a peripheral device coupled via USB).

[0049] In addition, the communication component 234 can detect the identifier, or include a component that is operable to detect the identifier. For example, the communication component 234 can include a radio frequency identification (RFID) tag reader component, an NFC smart tag detection component, an optical reader component (e.g., an optical sensor for detecting one-dimensional bar codes such as universal product codes (UPC) bar codes, multi-dimensional bar codes such as quick response (QR) codes, Aztec codes, data matrix, data symbols (Dataglyph), MaxiCode, PDF417, UltraCode, UCC RSS-2D bar codes, and other optical codes) or an acoustic detection component (e.g., a microphone for identifying an audio signal of a tag). In addition, various information can be obtained via the communication component 234, such as positioning obtained via Internet Protocol (IP) geolocation, location obtained via Internet Protocol (IP) geolocation, Positioning derived from signal triangulation, positioning derived from detecting NFC beacon signals that can indicate a specific location, etc.

[0050] Various memories (e.g., main memory 216, static memory 240, and memory of processor 204) and storage unit 218 may store one or more sets of instructions and data structures (e.g., software) embodied or used by any one or more of the methods or functions described herein. These instructions (e.g., instructions 202) when executed by processor 204 cause various operations to implement the disclosed examples.

[0051] Instructions 202 may be sent or received over network 236 using a transmission medium via a network interface device (e.g., a network interface component included in communications component 234) and using any of a number of well-known transmission protocols (e.g., Hypertext Transfer Protocol (HTTP)). Similarly, instructions 202 may be sent or received via a coupling (e.g., a peer-to-peer coupling) to device 238 using a transmission medium.

[0052] According to some examples, Figure 3A and Figure 3B is a graphic representation of the AR user interface. Figure 3C is a collaboration diagram of the components of the AR system that provide the AR user interface, and Figure 3D is an activity diagram of gesture and hand pose detection methods used by an AR system to provide user input to an AR user interface. Figure 3C As shown, AR system 352 includes a hand tracking pipeline 348 that captures video frame tracking data 330 of gestures and hand poses 334 being made by user 332 as user 332 interacts with AR application 328 .

[0053] exist Figure 3D In operation 302, an AR application 328 (such as an AR system 352) Figure 3C ) provides an AR user interface 318 to a user 332. The AR user interface 318 includes one or more virtual 3D objects 320, such as Figure 3A and Figure 3B As shown, a user 332 interacts with the one or more virtual 3D objects 320 to provide input into the AR user interface 318 .

[0054] In operation 304, the AR system 352 captures video frame tracking data 330 of the forearm, wrist, and hand 322 of the user 332 from the perspective of the user 332. To capture the video frame tracking data 330, the AR system 352 uses one or more cameras of the camera component 326 of the AR system 352, such as Figure 1A The camera component 326 generates video frame tracking data 330 based on the captured video data of gestures and hand gestures 334 being made by the user 332. The video frame tracking data 330 includes video data of the detectable portions of the forearm, wrist, and hand 322 of the user 332 as the user 332 makes the gestures and hand gestures 334 while interacting with the AR user interface 318. The camera component 326 transmits the video frame tracking data 330 to the skeletal 3D model inference component 324 and the dynamic filter parameter component 342, as shown. Figure 3C shown.

[0055] In operation 308, the skeletal 3D model inference component 324 receives the video frame tracking data 330 from the camera component 326 and generates skeletal 3D model data 338 based on the video frame tracking data 330. For example, the skeletal 3D model inference component 324 identifies landmark features on the forearm, wrist, and hand 322 of the user 332 captured in the video frame tracking data 330. The skeletal 3D model inference component 324 generates data of a sequence of skeletal 3D models (e.g., skeletal 3D model 366 and skeletal 3D model 370) in a 3D coordinate system based on the landmark features. The skeletal 3D model includes skeletal 3D model features, such as skeletal 3D model feature 368, skeletal 3D model feature 368, and skeletal 3D model feature 372, which correspond to the identified visual landmarks of the forearm, wrist, and hand 322 of the user 332. In some examples, the skeletal 3D model data 338 includes landmark data, such as landmark identification, physical location of landmarks, segmentation between joints of user's fingers, and classification information of one or more landmarks associated with the forearm, wrist and hand 322. For example, the skeletal 3D model inference component 324 generates the skeletal 3D model data 338 based on the video frame tracking data 330 using an artificial intelligence method and an ML hand tracking model 336 previously generated using a machine learning method. In some examples, the ML hand tracking model 336 includes, but is not limited to, a neural network, a learning vector quantization network, a logistic regression model, a support vector machine, a random decision forest, a naive Bayes model, a linear discriminant analysis model, and a K nearest neighbor model. In some examples, the machine learning method used to generate the ML hand tracking model 336 may include, but is not limited to, supervised learning, unsupervised learning, semi-supervised learning, reinforcement learning, dimensionality reduction, self-learning, feature learning, sparse dictionary learning, and anomaly detection.

[0056] In some examples, the ML hand tracking model 336 is trained to recognize combinations of wrist and knuckle positions that indicate gestures and hand gestures. In some examples, the ML hand tracking model 336 is trained to recognize gestures and hand gestures independently of video frame tracking data that emphasizes data of fingertips when gestures and hand gestures are made. In some examples, the ML hand tracking model 336 is trained to recognize the shoulder position of user 332 while user 332 is making gestures and hand gestures. In some examples, the training data set used to train the ML hand tracking model 336 is annotated so that knuckle features do not move during a pinch gesture, thereby increasing the invariance measure of some hand features during a pinch gesture being made by user 332.

[0057] In operation 306, the camera component 326 transmits the video frame tracking data 330 to the dynamic filter parameter component 342. The dynamic filter parameter component 342 receives the video frame tracking data 330 and generates skeletal 3D model filter parameter data 364 for the skeletal 3D model filtering component 360 based on the video frame tracking data 330. In some examples, the skeletal 3D model filtering component 360 uses a temporal filter to smooth or filter the skeletal 3D model data 338 generated by the skeletal 3D model inference component 324 to eliminate jitter in the skeletal 3D model 366 of the pose or hand gesture being made by the user 332, as described more fully below. The skeletal 3D model filter parameter data 364 includes, but is not limited to, the degree of filtering applied by the skeletal 3D model filtering component 360 to the skeletal 3D model data 338.

[0058] The dynamic filter parameter component 342 also generates target filter parameter data 350 for the target filter component 340 based on the video frame tracking data 330. In some examples, the target filter component 340 uses a temporal filter to smooth or filter the target data 356 generated by the target filter component 340 to eliminate jitter in the determined target location of the target virtual 3D object or the gesture or hand gesture being made by the user 332, as described more fully below. The target filter parameter data 350 includes, but is not limited to, the degree of filtering that the target filter component 340 will apply to the target data 356.

[0059] In some examples, the dynamic filter parameter component 342 generates target filter parameter data 350 and skeletal 3D model filter parameter data 364 based on the video frame tracking data 330 using an artificial intelligence method and one or more ML filter parameter models 344 previously generated using a machine learning method. In some examples, the ML filter parameter models include, but are not limited to, neural networks, learning vector quantization networks, logistic regression models, support vector machines, random decision forests, naive Bayes models, linear discriminant analysis models, and K nearest neighbor models. In some examples, the machine learning methods used to generate the ML filter parameter models may include, but are not limited to, supervised learning, unsupervised learning, semi-supervised learning, reinforcement learning, dimensionality reduction, self-learning, feature learning, sparse dictionary learning, and anomaly detection.

[0060] In operation 310, as Figure 3CAs shown, the skeleton 3D model filtering component 360 receives the skeleton 3D model data 338 and the skeleton 3D model filter parameter data 364, and uses a time filter to generate filtered skeleton 3D model data 362 based on the skeleton 3D model data 338 according to the skeleton 3D model filter parameter data 364. For example, the skeleton 3D model data 338 includes a time series of skeleton 3D models (e.g., skeleton 3D model 366 and skeleton 3D model 370), and the skeleton 3D model includes skeleton 3D model features (e.g., skeleton 3D model feature 368, skeleton 3D model feature 368, and skeleton 3D model feature 372). Each skeleton 3D model feature includes skeleton 3D model feature 3D coordinate data that defines the positioning of the skeleton 3D model feature in the 3D coordinate system. For each skeletal 3D model feature Xn (where n represents the position of the input skeletal 3D model feature in the time series of the corresponding skeletal 3D model feature) input to the skeletal 3D model filtering component 360, the temporal filter of the skeletal 3D model filtering component 360 generates a filtered skeletal 3D model feature X'n in the filtered target data 346.

[0061] In some examples, the temporal filter has various adjustable dynamic filter parameters included in the target filter parameter data 350, such as, but not limited to, a number of previous skeletal 3D model features for averaging, a weight of a current or previous skeletal 3D model feature applied to a sequence of skeletal 3D model features, etc. The degree of filtering is adjusted by setting the target filter parameter data 350, and the degree of filtering is the strength of smoothing or filtering the temporal sequence of skeletal 3D model features by the temporal filter.

[0062] In some examples, the temporal filter of the skeletal 3D model filtering component 360 averages the skeletal 3D model feature 3D coordinate data of the skeletal 3D model feature with the skeletal 3D model feature 3D coordinate data of the previously input skeletal 3D model feature to generate a filtered skeletal 3D model feature X'n in the filtered target data 346, where X'n = (Xn + Xn-1) / 2. In order to increase the degree of smoothing or filtering, the previous two skeletal 3D model features of the sequence of skeletal 3D model features are used for averaging. In order to reduce the amount of smoothing or filtering, the current target 3D coordinate data of the current skeletal 3D model feature value can be weighted to favor the current skeletal 3D model feature by a factor that is larger than the factor applied to one or more of the previous skeletal 3D model features in the sequence of skeletal 3D model features.

[0063] In some examples, the temporal filter of the skeletal 3D model filtering component 360 comprises a low pass filter. In some examples, the temporal filter of the skeletal 3D model filtering component 360 with adjustable parameters comprises a Kalman filter, a 1-Euro filter, and the like.

[0064] In some examples, the dynamic filter parameter component 342 determines the degree of smoothing or filtering applied to the skeleton 3D model data 338 based on the probability of a specific posture or hand gesture starting. In some examples, the degree of smoothing or filtering is proportional to the probability of a specific posture or hand gesture starting. For example, the greater the degree of smoothing or filtering applied to the skeleton 3D model data 338, the greater the probability of a specific posture or hand gesture starting, and the smaller the degree of filtering or smoothing applied to the skeleton 3D model data 338 by the skeleton 3D model filtering component 360, the smaller the probability of a specific posture or hand gesture starting. In some examples, the degree of smoothing or filtering is inversely proportional to the probability that a specific posture or hand gesture is about to occur. For example, the smaller the degree of smoothing or filtering applied to the skeleton 3D model data 338, the greater the probability of a specific posture or hand gesture starting, and the greater the degree of filtering or smoothing applied to the skeleton 3D model data 338 by the skeleton 3D model filtering component 360, the smaller the probability of a specific posture or hand gesture starting.

[0065] In some examples, the probability of a pinch gesture or hand gesture starting is determined by the dynamic filter parameter component 342 based on the following: Figure 3A 376 of the thumb of the user 332. The probability of a pinch gesture or hand gesture starting is proportional to the relative speed, that is, the greater the relative speed, the greater the probability of the gesture or hand gesture starting.

[0066] In some examples, the skeletal 3D model filtering component 360 applies differential smoothing or filtering to specific skeletal 3D model features of the skeletal 3D model. For example, the skeletal 3D model filtering component 360 applies a greater degree of smoothing or filtering to the (first) skeletal 3D model feature 384 corresponding to the finger joint 386 than the skeletal 3D model filtering component 360 applies a greater degree of smoothing or filtering to the (second) skeletal 3D model feature 372 corresponding to the distal phalanx 374 of the index finger.

[0067] In operation 312, the target component 354 receives the filtered skeletal 3D model data 362 and determines a target virtual 3D object or apparent target location in the AR user interface 318 provided by the AR application 328 based on the filtered skeletal 3D model data 362 and the AR user interface model 358 generated by the AR application 328. For example, the AR application 328 generates one or more virtual 3D objects, such as the virtual 3D object 320, included in the AR user interface model 358. The one or more virtual 3D objects comprise interactive components of the AR user interface 318 provided to the user 332 by the AR application 328. The one or more virtual 3D objects are rendered in 3D and are displayed using Figure 1A and Figure 1B The display device of the head wearable device 100 is displayed to the user 332 as part of the AR overlay. The user 332 interacts with one or more virtual 3D objects by selecting and manipulating virtual 3D objects using gestures and hand postures 334. The one or more virtual 3D objects are represented in the AR user interface model 358 using 3D coordinates in the 3D coordinate system of the AR user interface model 358. In a similar manner, the filtered skeletal 3D model data 362 includes a time series of skeletal 3D models, wherein the skeletal 3D model includes skeletal 3D model features, wherein each skeletal 3D model feature has a set of 3D coordinates in a common 3D coordinate system of the AR user interface model 358.

[0068] In some examples, a target virtual 3D object for a gesture being made by user 332 is determined based on a distance between one or more specific nodes of the skeletal 3D model and the virtual 3D object. For example, the specific node of the skeletal 3D model may be a skeletal 3D model feature such as skeletal 3D model feature 372 corresponding to distal phalanx 374 of index finger of user 332. Target component 354 calculates a 3D Euclidean distance between the specific skeletal 3D model feature and each virtual 3D object in AR user interface model 358. Target component 354 determines the virtual 3D object having the shortest distance to the specific skeletal 3D model feature as the target virtual 3D object.

[0069] In some examples, in a method known as “ray casting,” a virtual ray 382 is cast outward from a skeletal 3D model feature 378 of skeletal 3D model 366, and virtual 3D object 320 is determined as a target virtual 3D object based on an intersection 380 between virtual 3D object 320 and virtual ray 382. In some examples, skeletal 3D model feature 378 corresponds to the palm of user 332. In some examples, skeletal 3D model feature 378 represents the center of the user's hand.

[0070] In some examples, the target virtual 3D object is determined based on generating a virtual line segment between a (first) skeletal 3D model feature 372 corresponding to a distal phalanx 374 of an index finger of the user 332 and a (second) skeletal 3D model feature 368 corresponding to a distal phalanx 376 of a thumb of the user 332. The target virtual 3D object is determined based on an intersection between the virtual line segment and a virtual 3D object from among the one or more virtual 3D objects.

[0071] In some examples, a target virtual 3D object is determined based on the endpoint of a pinch gesture being made by user 332, where the endpoint is determined when the virtual 3D object 320, a (first) skeletal 3D model feature 372 corresponding to a distal phalanx 374 of an index finger of user 332, and a (second) skeletal 3D model feature 368 corresponding to a distal phalanx 376 of a thumb of user 332 are connected.

[0072] In some examples, the apparent target location is determined based on generating a virtual line segment between a (first) skeletal 3D model feature 372 corresponding to a distal phalanx 374 of an index finger of the user 332 and a (second) skeletal 3D model feature 368 corresponding to a distal phalanx 376 of a thumb of the user 332. The apparent target location is determined based on a midpoint of the virtual line segment.

[0073] In some examples, the apparent target location is determined based on the endpoints of a pinch gesture being made by user 332, where the endpoint is determined when a (first) skeletal 3D model feature 372 corresponding to a distal phalanx 374 of an index finger of user 332 and a (second) skeletal 3D model feature 368 corresponding to a distal phalanx 376 of a thumb of user 332 are connected.

[0074] In some examples, target data 356 includes 3D coordinate data of a target virtual 3D object or apparent target location within the 3D coordinate system of AR user interface model 358. In some examples, target data 356 includes metadata, such as an identifier, etc., of the target virtual 3D object.

[0075] In some examples, the target component 354 applies a hysteresis function based on a previous state determined by the target virtual 3D object during the determination of the target virtual 3D object of the posture or hand gesture. For example, in a method in which the target component 354 determines the target virtual 3D object based on the distance between the specific skeletal 3D model feature of the skeletal 3D model and the virtual 3D object (where the virtual 3D object closest to the specific skeletal 3D model feature is determined as the target virtual 3D object), the advantage or reward is applied to the currently determined target virtual 3D object by reducing the calculated distance between the specific skeletal 3D model feature and the currently selected target virtual 3D object. In some examples, the calculated distance is reduced by a fixed amount in units of the distance of the AR user interface model 358. In some examples, the calculated distance is reduced by a factor such as a percentage or ratio.

[0076] In some examples, target component 354 receives skeletal 3D model data 338 that has not been filtered by skeletal 3D model filtering component 360 , and generates target data 356 based on the unfiltered skeletal 3D model data 338 .

[0077] In operation 314, the target filter component 340 receives the target data 356 and the target filter parameter data 350, and generates filtered target data 346 based on the target data 356 using the time filter according to the target filter parameter data 350 of the time filter. In some examples, the target data 356 includes a time series of target 3D coordinate data of the target positioning and target virtual 3D object (collectively referred to as the target) as determined by the target component 354. For each specific target An (where n represents the position of the input target in the time series of the target) input to the target filter component 340, the time filter generates the target 3D coordinate data of the target using the target 3D coordinate data of the previously input target to generate the output target A'n in the filtered target data 346. The time filter has various adjustable dynamic filter parameters included in the target filter parameter data 350. The filtering degree is adjusted by setting the target filter parameter data 350, and the filtering degree is the strength of the smoothing or filtering of the time series of the node by the time filter.

[0078] In some examples, the temporal filter averages the target 3D coordinate data of the target with the target 3D coordinate data of the previously input target to generate the output target, or A'n = (An + An-1) / 2. The temporal filter has various adjustable dynamic filter parameters included in the target filter parameter data 350, such as but not limited to multiple previous targets for averaging, weights applied to the current or previous targets, etc. For example, to increase the degree of smoothing or filtering, the previous two targets of the sequence of targets are used for averaging. In order to reduce the amount of smoothing or filtering, the current target 3D coordinate data of the current target can be weighted to favor the current target by a factor larger than the factor applied to one or more of the previous targets in the sequence of targets.

[0079] In some examples, the temporal filter of the target filter component 340 comprises a low pass filter. In some examples, the temporal filter of the target filter component 340 with adjustable parameters comprises a Kalman filter, a Euro 1 filter, or the like.

[0080] In some examples, the degree of smoothing or filtering applied to the target data 356 by the target filter component 340 is determined by the dynamic filter parameter component 342 based on the probability of a particular posture or hand gesture starting. In some examples, the degree of smoothing or filtering is proportional to the probability of a particular posture or hand gesture starting. For example, the greater the degree of smoothing or filtering applied to the target data 356, the greater the probability of a particular posture or hand gesture starting, and the smaller the degree of filtering or smoothing applied to the target data 356 by the target filter component 340, the smaller the probability of a particular posture or hand gesture starting. In some examples, the degree of smoothing or filtering is inversely proportional to the probability that a particular posture or hand gesture is about to occur. For example, the smaller the degree of smoothing or filtering applied to the target data 356, the greater the probability of a particular posture or hand gesture starting, and the greater the degree of filtering or smoothing applied to the target data 356 by the target filter component 340, the smaller the probability of a particular posture or hand gesture starting.

[0081] In operation 316, the hand tracking pipeline provides the filtered target data 346 to the AR application 328. The AR application 328 receives the filtered target data 346 and uses the filtered target data 346 as user input for additional operations of the AR application.

[0082] Networked computing environment

[0083] Figure 44 is a block diagram illustrating an example interactive system 400 for facilitating interactions over a network (e.g., exchanging text messages, making text audio and video calls, or playing games). The interactive system 400 includes multiple AR systems 402, each of which hosts multiple applications including an interactive client 404 and other applications 406. Each interactive client 404 is communicatively coupled to other instances of the interactive client 404 (e.g., hosted on corresponding other AR systems 402), an interactive server system 410, and a third-party server 412 via one or more communication networks including a network 408 (e.g., the Internet). The interactive client 404 can also communicate with the locally hosted application 406 using an application program interface (API).

[0084] Each computing system 402 may include one or more user devices, such as a mobile device 414 , a head wearable device 100 , and a computer client device 416 , which are communicatively connected to exchange data and messages.

[0085] The interactive clients 404 interact with other interactive clients 404 and with an interactive server system 410 via the network 408. Data exchanged between the interactive clients 404 (e.g., interaction 418) and between the interactive clients 404 and the interactive server system 410 includes functions (e.g., commands for activating functions) and payload data (e.g., text, audio, video, or other multimedia data).

[0086] The interactive server system 410 provides server-side functions to the interactive client 404 via the network 408. Although certain functions of the interactive system 400 are described herein as being performed by the interactive client 404 or by the interactive server system 410, the location of certain functions within the interactive client 404 or within the interactive server system 410 may be a design choice. For example, it may be technically preferred to initially deploy certain technologies and functions within the interactive server system 410, but later migrate the technologies and functions to the interactive client 404 where the computing system 402 has sufficient processing power.

[0087] The interactive server system 410 supports various services and operations provided to the interactive clients 404. Such operations include sending data to the interactive clients 404, receiving data from the interactive clients 404, and processing data generated by the interactive clients 404. The data may include message content, client device information, geolocation information, media enhancements and overlays, message content persistence conditions, social network information, and live event information. The data exchange within the interactive system 400 is activated and controlled by functions available through the user interface (UI) of the interactive client 404.

[0088] Turning now specifically to the interaction server system 410, an application program interface (API) server 420 is coupled to and provides a programming interface to an interaction server 422, making the functionality of the interaction server 422 accessible to the interaction clients 404, other applications 406, and third-party servers 412. The interaction server 422 is communicatively coupled to a database server 424, thereby facilitating access to a database 426 that stores data associated with interactions processed by the interaction server 422. Similarly, a web server 428 is coupled to the interaction server 422 and provides a web-based interface to the interaction server 422. To this end, the web server 428 handles incoming network requests via the Hypertext Transfer Protocol (HTTP) and several other related protocols.

[0089] The application program interface (API) server 420 receives and sends interaction data (e.g., commands and message payloads) between the interaction server 422 and the AR system 402 (and, for example, the interaction client 404 and other applications 406) and the third-party server 412. Specifically, the application program interface (API) server 420 provides a set of interfaces (e.g., routines and protocols) that the interaction client 404 and other applications 406 can call or query to activate the functions of the interaction server 422. The application program interface (API) server 420 exposes various functions supported by the interaction server 422, including account registration; login functionality; sending interaction data from a particular interaction client 404 to another interaction client 404 via the interaction server 422; transferring media files (e.g., images or videos) from the interaction client 404 to the interaction server 422; setting up a collection of media data (e.g., a story); retrieving a friend list of a user of the computing system 402; retrieving messages and content; adding and removing entities (e.g., friends) from an entity graph (e.g., a social graph); locating friends within a social graph; and opening application events (e.g., related to the interaction client 404).

[0090] Interactive server 422 hosts multiple systems and subsystems, see below Figure 7 Give a description.

[0091] Linked Applications

[0092] Returning to the interactive client 404, the features and functions of the external resource (e.g., the linked application 406 or applet) are available to the user via the interface of the interactive client 404. In this context, "external" refers to the fact that the application 406 or applet is outside the interactive client 404. Although the external resource is usually provided by a third party, it can also be provided by the creator or provider of the interactive client 404. The interactive client 404 receives a user selection of an option for launching or accessing the features of such an external resource. The external resource can be an application 406 (e.g., a "native app") installed on the computing system 402, or a small-scale version of the application (e.g., a "mini program") hosted on the computing system 402 or located at the far end of the computing system 402 (e.g., on a third-party server 412). The small-scale version of the application includes a subset of the features and functions of the application (e.g., a full-scale native version of the application) and is implemented using a markup language document. In some examples, the small-scale version of the application (e.g., a "mini program") is a web-based markup language version of the application and is embedded in the interactive client 404. In addition to using markup language documents (eg, .*ml files), applets may include scripting languages ​​(eg, .*js files or .json files) and style sheets (eg, .*ss files).

[0093] In response to receiving a user selection of an option for launching or accessing a feature of an external resource, the interactive client 404 determines whether the selected external resource is a web-based external resource or a locally installed application 406. In some cases, the application 406 installed locally on the computing system 402 can be independent of the interactive client 404 and launched separately from the interactive client 404, such as by selecting an icon corresponding to the application 406 on a home screen of the computing system 402. A small-scale version of such an application can be launched or accessed via the interactive client 404, and in some examples, no portion of the small-scale application can be accessed outside of the interactive client 404 or only a limited portion of the small-scale application can be accessed outside of the interactive client 404. The small-scale application can be launched by the interactive client 404 receiving, for example, a markup language document associated with the small-scale application from the third-party server 412 and processing such a document.

[0094] In response to determining that the external resource is a locally installed application 406, the interactive client 404 instructs the computing system 402 to launch the external resource by executing the locally stored code corresponding to the external resource. In response to determining that the external resource is a web-based resource, the interactive client 404 communicates with the third-party server 412 (for example) to obtain a markup language document corresponding to the selected external resource. The interactive client 404 then processes the obtained markup language document to present the web-based external resource within the user interface of the interactive client 404.

[0095] Interactive client 404 can notify the user of computing system 402 or other users (e.g., "friends") related to such users of one or more external resources of activities taking place. For example, interactive client 404 can provide participants of a conversation (e.g., a chat session) in interactive client 404 with notifications related to external resources currently or recently used by one or more members of a group of users. One or more users can be invited to join an active external resource or start an external resource that is recently used but currently inactive (in the group of friends). External resources can provide participants of the conversation who use the corresponding interactive client 404 to share items, conditions, states, or locations in the external resource with one or more members of a group of users in the chat session. The shared items can be interactive chat cards, and members of the chat can interact with the interactive chat cards to, for example, start the corresponding external resource, view specific information in the external resource, or bring members of the chat to a specific location or state in the external resource. Within a given external resource, a response message can be sent to a user on interactive client 404. The external resource can selectively include different media items in the response based on the current context of the external resource.

[0096] The interactive client 404 can present a list of available external resources (e.g., applications 406 or applets) to the user to launch or access a given external resource. The list can be presented in a context-sensitive menu. For example, icons representing different applications (or applets) of the application 406 (or applets) can vary based on how the user launches the menu (e.g., from a conversational interface or from a non-conversational interface).

[0097] System with head wearable device

[0098] Figure 5 A system 500 is shown including a head wearable device 100 with a selector input device according to some examples. Figure 5 is a high-level functional block diagram of an example head wearable device 100 communicatively coupled to a mobile device 414 and various server systems 504 (e.g., an interactive server system 410) via various networks 408.

[0099] The head wearable device 100 includes one or more camera devices, each of which may be, for example, a visible light camera 508, an infrared transmitter 510, and an infrared camera 512.

[0100] The mobile device 414 is connected to the head wearable device 100 using both a low power wireless connection 514 and a high speed wireless connection 516. The mobile device 414 is also connected to the server system 504 and the network 506.

[0101] The head wearable device 100 also includes two image displays in the image display 518 of the optical assembly. The two image displays 518 of the optical assembly include one image display associated with the left lateral side of the head wearable device 100 and one image display associated with the right lateral side of the head wearable device 100. The head wearable device 100 also includes an image display driver 520 and a GPU 522. The image display 518 of the optical assembly, the image display driver 520, and the GPU 522 constitute the optical engine, low power circuitry 524, and high speed circuitry 526 of the head wearable device 100. The image display 518 of the optical assembly is used to present images and videos to a user of the head wearable device 100, including images that may include a graphical user interface.

[0102] The image display driver 520 commands and controls the image display 518 of the optical assembly. The image display driver 520 can deliver the image data directly to the image display 518 of the optical assembly for presentation or can convert the image data into a signal or data format suitable for delivery to the image display device. For example, the image data can be video data formatted according to a compression format such as H.264 (MPEG-4 Part 10), HEVC, Theora, Dirac, RealVideo RV40, VP8, VP9, ​​etc., and the still image data can be formatted according to a compression format such as Portable Network Graphics Group (PNG), Joint Photographic Experts Group (JPEG), Tagged Image File Format (TIFF) or Exchangeable Image File Format (EXIF), etc.

[0103] The head wearable device 100 includes a frame and rods (or temples) extending from lateral sides of the frame. The head wearable device 100 also includes a user input device 528 (e.g., a touch sensor or a push button) including an input surface on the head wearable device 100. The user input device 528 (e.g., a touch sensor or a push button) is used to receive input selections from a user to manipulate a graphical user interface of a presented image.

[0104] Figure 5 The components for the head wearable device 100 shown in the figure are located on one or more circuit boards, such as a PCB or a flexible PCB, in the frame or temples. Alternatively or additionally, the depicted components may be located in a block, frame, hinge, or nose bridge of the head wearable device 100. The left visible light camera 508 and the right visible light camera 508 may include digital camera elements, such as complementary metal oxide semiconductor (CMOS) image sensors, charge coupled devices, camera lenses, or any other corresponding visible light or light capturing elements that can be used to capture data (including images of scenes with unknown objects).

[0105] The head wearable device 100 includes a memory 502 that stores instructions for performing a subset or all of the functions described herein. The memory 502 may also include a storage device.

[0106] like Figure 5 As shown, the high-speed circuit system 526 includes a high-speed processor 530, a memory 502, and a high-speed wireless circuit system 532. In some examples, the image display driver 520 is coupled to the high-speed circuit system 526 and is operated by the high-speed processor 530 to drive the left image display and the right image display of the image display 518 of the optical assembly. The high-speed processor 530 can be any processor capable of managing high-speed communications and operations of any general computing system required for the head wearable device 100. The high-speed processor 530 includes the processing resources required to manage the high-speed data transmission on the high-speed wireless connection 516 to the wireless local area network (WLAN) using the high-speed wireless circuit system 532. In some examples, the high-speed processor 530 executes an operating system of the head wearable device 100, such as a LINUX operating system or other such operating system, and the operating system is stored in the memory 502 for execution. In addition to any other duties, the high-speed processor 530 that executes the software architecture for the head wearable device 100 is used to manage data transmission with the high-speed wireless circuit system 532. In some examples, high-speed wireless circuit system 532 is configured to implement the Institute of Electrical and Electronics Engineers (IEEE) 802.11 communication standard, also referred to herein as WiFi. In some examples, high-speed wireless circuit system 532 can implement other high-speed communication standards.

[0107] The low-power wireless circuit system 534 and the high-speed wireless circuit system 532 of the head wearable device 100 may include a short-range transceiver (Bluetooth TM ) and a wireless wide area network, local area network, or wide area network transceiver (e.g., cellular or WiFi). Mobile device 414 - including a transceiver that communicates via low power wireless connection 514 and high speed wireless connection 516 - can be implemented using details of the architecture of head wearable device 100, and can also be implemented using other elements of network 506.

[0108] The memory 502 includes any storage device capable of storing various data and applications, in addition to camera data generated by the left and right visible light cameras 508, the infrared camera 512, and the GPU 522, and images generated by the image display driver 520 for display on the image display 518 of the optical assembly. Although the memory 502 is shown as being integrated with the high-speed circuit system 526, in some examples, the memory 502 can be a separate independent element of the head wearable device 100. In some such examples, electrical wiring can provide a connection from the GPU 522 or the low-power processor 536 to the memory 502 through a chip including the high-speed processor 530. In some examples, the high-speed processor 530 can manage the addressing of the memory 502 so that the low-power processor 536 will start the high-speed processor 530 whenever a read or write operation involving the memory 502 is required.

[0109] like Figure 5 As shown in , the low-power processor 536 or the high-speed processor 530 of the head wearable device 100 can be coupled to a camera device (a visible light camera device 508, an infrared emitter 510 or an infrared camera device 512), an image display driver 520, a user input device 528 (for example, a touch sensor or a push button), and a memory 502.

[0110] The head wearable device 100 is connected to a host computer. For example, the head wearable device 100 is paired with the mobile device 414 via a high-speed wireless connection 516 or connected to a server system 504 via a network 506. The server system 504 can be one or more computing devices as part of a service or network computing system, for example, including a processor, a memory, and a network communication interface to communicate with the mobile device 414 and the head wearable device 100 through the network 506.

[0111] The mobile device 414 includes a processor and a network communication interface coupled to the processor. The network communication interface allows communication via the network 506, the low-power wireless connection 514, or the high-speed wireless connection 516. The mobile device 414 may also store at least part of the instructions for generating two-channel audio content in a memory of the mobile device 414 to implement the functions described herein.

[0112] The output components of the head wearable device 100 include visual components, such as displays such as liquid crystal displays (LCDs), plasma display panels (PDPs), light emitting diode (LED) displays, projectors, or waveguides. The image display of the optical assembly is driven by an image display driver 520. The output components of the head wearable device 100 also include acoustic components (e.g., speakers), tactile components (e.g., vibration motors), other signal generators, etc. The input components of the head wearable device 100, the mobile device 414, and the server system 504, such as user input devices 528, may include alphanumeric input components (e.g., keyboards, touch screens configured to receive alphanumeric input, optical keyboards, or other alphanumeric input components), point-based input components (e.g., mice, touch pads, trackballs, joysticks, motion sensors, or other pointing instruments), tactile input components (e.g., physical buttons, touch screens or other tactile input components that provide positioning and force of touch or touch gestures), audio input components (e.g., microphones), etc.

[0113] The head wearable device 100 may also include additional peripheral elements. Such peripheral elements may include biometric sensors, additional sensors, or display elements integrated with the head wearable device 100. For example, the peripheral elements may include any I / O components including output components, motion components, position components, or any other such components described herein.

[0114] For example, the biometric component includes a component for detecting expressions (e.g., hand expressions, facial expressions, voice expressions, body postures, or eye tracking), measuring biological signals (e.g., blood pressure, heart rate, body temperature, sweating, or brain waves), identifying people (e.g., voice recognition, retinal recognition, facial recognition, fingerprint recognition, or electroencephalogram-based recognition), etc. The motion component includes an acceleration sensor component (e.g., an accelerometer), a gravity sensor component, a rotation sensor component (e.g., a gyroscope), etc. The position component includes a positioning sensor component for generating positioning coordinates (e.g., a global positioning system (GPS) receiver component), a Wi-Fi or Bluetooth receiver component for generating positioning system coordinates, etc. TM transceiver, altitude sensor component (e.g., an altimeter or barometer that detects air pressure, from which altitude can be obtained), orientation sensor component (e.g., a magnetometer), etc. Such positioning system coordinates can also be received from mobile device 414 via low-power wireless connection 514 and high-speed wireless connection 516 via low-power wireless circuit system 534 or high-speed wireless circuit system 532.

[0115] Data Architecture

[0116] Figure 66 is a schematic diagram illustrating a data structure 600 that may be stored in a database 604 of an interactive server system 410 according to some examples. Although the contents of the database 604 are illustrated as including a plurality of tables, it will be appreciated that data may be stored in other types of data structures (e.g., as an object-oriented database).

[0117] Database 604 includes message data stored in message table 606. For any particular message, the message data includes at least message sender data, message recipient (or receiver) data, and payload. Figure 6 Additional details regarding information that may be included in a message and included within the message data stored in message table 606 are described.

[0118] The entity table 608 stores entity data and is linked (e.g., referenced) to the entity graph 610 and the profile data 602. The entities whose records are maintained within the entity table 608 may include individuals, corporate entities, organizations, objects, places, events, etc. Regardless of the entity type, any entity about which the interactive server system 410 stores data may be an identified entity. Each entity is provided with a unique identifier and an entity type identifier (not shown).

[0119] The entity graph 610 stores information about relationships and associations between entities. For example, such relationships can be interest-based or activity-based social relationships, professional relationships (e.g., working in a common company or organization). Some relationships between entities can be one-way, such as a personal user's subscription to a business or publishing user's digital content (e.g., a newspaper or other digital media channel or brand). Other relationships can be two-way, such as a "friend" relationship between various users of the interactive system 400.

[0120] Certain permissions and relationships can be attached to each relationship, and also to each direction of the relationship. For example, a two-way relationship (e.g., a friend relationship between various users) can include authorization for the disclosure of digital content items between various users, but certain restrictions or filters (e.g., based on content features, location data, or time of day data) can be imposed on the disclosure of these digital content items. Similarly, a subscription relationship between a personal user and a business user can impose varying degrees of restrictions on the disclosure of digital content from a business user to a personal user, and can greatly limit or prevent the disclosure of digital content from a personal user to a business user. As an example of an entity, a specific user can record certain restrictions in a record for the entity in the entity table 608 (e.g., by means of privacy settings). Such privacy settings can be applied to all types of relationships in the context of the interactive system 400, or can be selectively applied to only certain types of relationships.

[0121] Profile data 602 stores multiple types of profile data about a particular entity. Based on the privacy settings specified by the particular entity, profile data 602 can be selectively used and presented to other users of interactive system 400. In the case where the entity is a person, profile data 602 includes, for example, a user name, phone number, address, settings (e.g., notification and privacy settings), and an avatar representation (or a collection of such avatar representations) selected by the user. The particular user can then selectively include one or more of these avatar representations within the content of messages transmitted via interactive system 400 and on a map interface displayed to other users by interactive client 404. The collection of avatar representations can include a "status avatar" that presents a graphical representation of a state or activity that a user can select to convey at a particular time.

[0122] Where the entity is a group, profile data 602 for the group may similarly include one or more avatar representations associated with the group, in addition to the group name, members, and various settings for the relevant group (eg, notifications).

[0123] Database 604 also stores enhancement data, such as overlays or filters, in enhancement table 612. Enhancement data is associated with and applied to videos (data for videos is stored in video table 614) and images (data for images is stored in image table 616).

[0124] In some examples, the filter is an overlay displayed as an overlay on an image or video during presentation to the message recipient. The filter can be of various types, including a user-selected filter from a set of filters presented to the message sender by the interactive client 404 when the message sender is composing the message. Other types of filters include geolocation filters (also referred to as geofilters), which can be presented to the message sender based on geolocation. For example, a geolocation filter specific to a nearby or special location can be presented by the interactive client 404 within the user interface based on geolocation information determined by a global positioning system (GPS) unit of the computing system 402.

[0125] Another type of filter is a data filter, which can be selectively presented to the message sender by the interactive client 404 based on other input or information collected during the message creation process by the computing system 402. Examples of data filters include the current temperature at a particular location, the current speed at which the message sender is traveling, the battery life of the computing system 402, or the current time.

[0126] Other augmented data that may be stored in the image table 616 include augmented reality content items (eg, corresponding to application lenses or augmented reality experiences). Augmented reality content items may be real-time special effects and sounds that may be added to an image or video.

[0127] As described above, augmented data includes AR, VR, and mixed reality (MR) content items, overlays, image transformations, images, and modifications that can be applied to image data (e.g., videos or images). This includes real-time modifications that are modified by using a device sensor (e.g., one or more cameras) of the computing system 402 to capture an image and then modifying the image using the modification when the image is displayed on the screen of the computing system 402. This also includes modifications to stored content (e.g., video clips that can be modified in a collection or group). For example, in a computing system 402 that accesses multiple augmented reality content items, a user can use a single video clip with multiple augmented reality content items to see how different augmented reality content items will modify the stored clips. Similarly, real-time video capture can use modifications to show how the video image currently captured by the sensor of the computing system 402 will modify the captured data. Such data can be displayed only on the screen without being stored in memory, or the content captured by the device sensor can be recorded and stored in memory with or without modification (or both with and without modification). In some systems, a preview feature can simultaneously display how different augmented reality content items will look in different windows in the display. For example, this may enable multiple windows with different pseudo-random animations to be viewed simultaneously on the display.

[0128] Thus, data and various systems using augmented reality content items or other such transformation systems using the data to modify content may involve: detection of various objects (e.g., faces, hands, bodies, cats, dogs, surfaces, objects, etc.) in video frames, tracking of such objects as they leave, enter, and move around the field of view, and modification or transformation of such objects as they are tracked. In various examples, different methods for implementing such transformations may be used. Some examples may involve: generating a three-dimensional mesh model of one or more objects; and using transformations of the models and animated textures within the video to implement the transformations. In some examples, tracking of points on the objects may be used to place an image or texture (which may be two-dimensional or three-dimensional) at the tracked location. In yet another example, neural network analysis of video frames may be used to place an image, model, or texture in content (e.g., an image or video frame). Thus, augmented reality content items involve both images, models, and textures used to create transformations in the content, and additional modeling and analysis information required to implement such transformations using object detection, tracking, and placement.

[0129] Real-time video processing can be performed using any kind of video data (e.g., video streams, video files, etc.) stored in the memory of any kind of computerized system. For example, a user can load video files and store them in the memory of the device, or a sensor of the device can be used to generate a video stream. In addition, any object, such as a human face and parts of a human body, an animal, or a non-living thing (e.g., a chair, a car, or other objects) can be processed using computer animation models.

[0130] In some examples, when a specific modification is selected together with the content to be transformed, the element to be transformed is identified by a computing device, and then if the element to be transformed is present in a frame of the video, it is detected and tracked. The elements of the object are modified according to the modification request, thereby transforming the frame of the video stream. For different types of transformations, the frames of the video stream can be transformed by different methods. For example, for frame transformations that mainly involve changing the form of the elements of the object, characteristic points for each element of the object are calculated (for example, using an active shape model (ASM) or other known methods). Then, a grid based on the characteristic points is generated for each element of the object. The grid is used for subsequent stages of tracking the elements of the object in the video stream. During the tracking process, the grid for each element is aligned with the position of each element. Then, additional points are generated on the grid.

[0131] In some examples, the transformation of some areas of the object using the elements of the object can be performed by calculating the characteristic points for each element of the object and generating a grid based on the calculated characteristic points. Points are generated on the grid, and then various areas based on these points are generated. Then, the elements of the object are tracked by aligning the area of ​​each element with the position of each element of at least one element, and the properties of the area can be modified based on the modification request, thereby transforming the frame of the video stream. Depending on the specific modification request, the properties of the mentioned area can be transformed in different ways. Such modifications may involve: changing the color of the area; removing some parts of the area from the frame of the video stream; including new objects in the area based on the modification request; and modifying or distorting the elements of the area or object. In various examples, any combination of such modifications or other similar modifications may be used. For certain models to be animated, some characteristic points can be selected as control points to determine the entire state space of options for model animation.

[0132] In some examples of computer animation models for transforming image data using face detection, faces are detected on an image using a specific face detection algorithm (e.g., Viola-Jones). An active shape model (ASM) algorithm is then applied to the face region of the image to detect facial feature reference points.

[0133] Other methods and algorithms suitable for face detection can be used. For example, in some examples, virtual features are located using landmarks that represent distinguishable points that are present in most of the images considered. For example, for facial landmarks, the location of the left eye pupil can be used. If the initial landmark is not recognizable (for example, when a person has an eye mask), secondary landmarks can be used. Such a landmark recognition process can be used for any such object. In some examples, a set of landmarks forms a shape. The coordinates of the points in the shape can be used to represent the shape as a vector. One shape is aligned with another shape using a similarity transformation (allowing translation, scaling, and rotation) that minimizes the average Euclidean distance between the shape points. The mean shape is the average of the aligned training shapes.

[0134] The transformation system can capture an image or video stream on a client device (e.g., computing system 402) and perform complex image manipulations locally on computing system 402 while maintaining an appropriate user experience, computing time, and power consumption. Complex image manipulations can include size and shape changes, emotion transformations (e.g., changing a face from a frown to a smile), state transitions (e.g., aging a subject, reducing apparent age, changing gender), style transformations, application of graphical elements, and any other suitable image or video manipulations enabled by a convolutional neural network that has been configured to execute efficiently on computing system 402.

[0135] In some examples, a computer animation model for transforming image data can be used by a system in which a user can capture an image or video stream of the user (e.g., a selfie) using a computing system 402 having a neural network operating as part of an interactive client 404 operating on the computing system 402. The transformation system operating within the interactive client 404 determines the presence of a face within the image or video stream and provides a modification icon associated with the computer animation model to transform the image data, or the computer animation model can exist in association with an interface described herein. The modification icon includes changes as a basis for modifying the user's face within the image or video stream as part of the modification operation. Once the modification icon is selected, the transformation system initiates a process of transforming the user's image to reflect the selected modification icon (e.g., generating a smiley face on the user). Once the image or video stream is captured and the specified modification is selected, the modified image or video stream can be presented in a graphical user interface displayed on the computing system 402. The transformation system can implement a complex convolutional neural network on a portion of the image or video stream to generate and apply the selected modification. That is, a user can capture an image or video stream, and once a modification icon is selected, the modified result can be presented to the user in real time or near real time. Furthermore, while the video stream is being captured, the modification can be persistent and the selected modification icon remains toggled. Machine-taught neural networks can be used to implement such modifications.

[0136] The graphical user interface presenting the modifications performed by the transformation system can supply additional interactive options to the user. Such options can be based on the interface used to initiate the selection of a particular computer animation model and content capture (e.g., initiated from a content creator user interface). In various examples, the modifications can be persistent after the initial selection of the modification icon. The user can switch to turn the modification on or off by tapping or otherwise selecting the face modified by the transformation system, and store it for later viewing or browsing to other areas of the imaging application. In the case of multiple faces modified by the transformation system, the user can switch to turn the modification on or off globally by tapping or selecting a single face modified and displayed within the graphical user interface. In some examples, each face in a group of multiple faces can be modified individually, or such modifications can be switched individually by tapping or selecting a single face or a series of single faces displayed within the graphical user interface.

[0137] The story table 618 stores data about a collection of messages and associated images, video or audio data that are compiled into a collection (e.g., a story or gallery). The creation of a particular collection can be initiated by a particular user (e.g., each user for whom a record is maintained in the entity table 608). A user can create a "personal story" in the form of a collection of content that has been created and sent / broadcasted by the user. To this end, the user interface of the interactive client 404 can include a user-selectable icon to enable the message sender to add specific content to his or her personal story.

[0138] The collection may also constitute a "live story" as a collection of content from multiple users, created manually, automatically, or using a combination of manual and automatic techniques. For example, a "live story" may constitute a curated stream of user-submitted content from various locations and events. Users whose client devices have location services enabled and who are at a co-located event at a particular time may be presented with the option of contributing content to a particular live story, for example, via the user interface of the interactive client 404. Live stories may be identified to the user by the interactive client 404 based on his or her location. The end result is a "live story" told from a group perspective.

[0139] Another type of content collection is called a "location story" that enables users whose computing systems 402 are located within a specific geographic location (e.g., on a college or university campus) to contribute to a specific collection. In some examples, contributions to location stories may require secondary authentication to verify that the end user belongs to a specific organization or other entity (e.g., is a student on a university campus).

[0140] As mentioned above, video table 614 stores video data, which in some examples is associated with messages whose records are maintained within message table 606. Similarly, image table 616 stores image data associated with messages whose message data is stored in entity table 608. Entity table 608 may associate various enhancements from enhancement table 612 with various images and videos stored in image table 616 and video table 614.

[0141] Database 604 also includes social networking information collected by social networking system 722 .

[0142] System Architecture

[0143] Figure 74 is a block diagram showing additional details about an interactive system 400 according to some examples. Specifically, the interactive system 400 is shown to include an interactive client 404 and an interactive server 422. The interactive system 400 contains a number of subsystems that are supported on the client side by the interactive client 404 and on the server side by the interactive server 422. Example subsystems are discussed below.

[0144] Image processing system 702 provides various functions that enable a user to capture and enhance (eg, enhance or otherwise modify or edit) media content associated with a message.

[0145] The camera system 704 includes control software (e.g., in a camera application) that interacts with and controls the hardware camera hardware of the computing system 402 (e.g., directly or via operating system control) to modify and enhance real-time images captured and displayed via the interactive client 404.

[0146] The enhancement system 706 provides functionality related to the generation and publication of enhancements (e.g., media overlays) for images captured in real time by the camera of the computing system 402 or retrieved from the memory of the computing system 402. For example, the enhancement system 706 is operable to select, present, and display media overlays (e.g., image filters or image lenses) for the interactive client 404 for enhancing the real-time imagery received via the camera system 704 or the stored imagery retrieved from the memory 502 of the computing system 402. These enhancements are selected and presented to the user of the interactive client 404 by the enhancement system 706 based on some input and data, such as:

[0147] The geographic location of computing system 402; and

[0148] • Social network information of users of computing system 402 .

[0149] Enhancement can include audio and visual content and visual effects. Examples of audio and visual content include pictures, text, logos, animations, and sound effects. Examples of visual effects include color overlays. Audio and visual content or visual effects can be applied to media content items (e.g., photos or videos) at computing system 402 for transmission in messages, or applied to video content such as video content streams or feeds sent from interactive client 404. Therefore, image processing system 702 can interact with various subsystems of communication system 708 and support various subsystems of communication system 708, such as messaging system 710 and video communication system 712.

[0150] Media overlays may include text or image data that can be superimposed on a photo taken by computing system 402 or a video stream produced by computing system 402. In some examples, the media overlay may be a location overlay (e.g., Venice Beach), the name of a live event, or a business name overlay (e.g., Beach Cafe). In another example, image processing system 702 uses the geographic location of computing system 402 to identify a media overlay that includes a business name at the geographic location of computing system 402. Media overlays may include other tags associated with the business. Media overlays may be stored in database 426 and accessed by database server 424.

[0151] The image processing system 702 provides a user-based publishing platform that enables a user to select a geographic location on a map and upload content associated with the selected geographic location. The user can also specify the context in which a particular media overlay should be provided to other users. The image processing system 702 generates a media overlay that includes the uploaded content and associates the uploaded content with the selected geographic location.

[0152] The augmented creation system 714 supports the augmented reality developer platform and includes applications for content creators (e.g., artists and developers) to create and publish augmentations (e.g., augmented reality experiences) for the interactive clients 404. The augmented creation system 714 provides content creators with a library of built-in features and tools, including, for example, custom shaders, tracking techniques, and templates.

[0153] In some examples, the enhancement creation system 714 provides a merchant-based publishing platform that enables merchants to select specific enhancements associated with a geographic location via a bidding process. For example, the enhancement creation system 714 associates the media overlay of the highest bidding merchant with the corresponding geographic location for a predefined amount of time.

[0154] The communication system 708 is responsible for enabling and processing various forms of communication and interaction within the interactive system 400, and includes a messaging system 710, an audio communication system 716, and a video communication system 712. The messaging system 710 is responsible for implementing temporary or time-limited access to content by the interactive client 404. The messaging system 710 includes multiple timers (e.g., within a transient timer system 718) that selectively enable access (e.g., for presentation and display) of messages and associated content via the interactive client 404 based on duration and display parameters associated with a message or a collection of messages (e.g., a story). Additional details on the operation of the transient timer system 718 are provided below. The audio communication system 716 enables and supports audio communication (e.g., real-time audio chat) between multiple interactive clients 404. Similarly, the video communication system 712 enables and supports video communication (e.g., real-time video chat) between multiple interactive clients 404.

[0155] The user management system 720 is operationally responsible for managing user data and profiles, and includes a social networking system 722 that maintains social networking information regarding relationships between users of the interactive system 400 .

[0156] The collection management system 724 is operationally responsible for managing a collection or collection of media (e.g., a collection of text, image video, and audio data). A collection of content (e.g., messages, including images, videos, text, and audio) can be organized into an "event gallery" or "event story". Such a collection can be made available within a specified time period (e.g., the duration of the event to which the content relates). For example, content related to a concert can be made available as a "story" for the duration of the concert. The collection management system 724 can also be responsible for publishing an icon that provides notifications of a specific collection to the user interface of the interactive client 404. The collection management system 724 includes a curation function that enables collection managers to manage and curate specific content collections. For example, a curation interface enables event organizers to curate a collection of content related to a specific event (e.g., deleting inappropriate content or redundant messages). In addition, the collection management system 724 uses machine vision (or image recognition technology) and content rules to automatically curate content collections. In some examples, compensation can be paid to users for including user-generated content in a collection. In such a case, the collection management system 724 operates to automatically pay such users to use their content.

[0157] The mapping system 726 provides various geolocation functions and supports the presentation of map-based media content and messages by the interactive client 404. For example, the mapping system 726 enables the display of a user icon or avatar (e.g., stored in the profile data 602) on a map to indicate the current or past locations of the user's "friends" and media content (e.g., a collection of messages including photos and videos) generated by these friends within the context of the map. For example, on the map interface of the interactive client 404, messages posted by the user to the interactive system 400 from a particular geolocation can be displayed to the "friends" of the particular user within the context of that particular location on the map. The user can also share his or her location and status information with other users of the interactive system 400 via the interactive client 404 (e.g., using an appropriate status avatar), where the location and status information is similarly displayed to the selected user within the context of the map interface of the interactive client 404.

[0158] The gaming system 728 provides various gaming functions within the context of the interactive client 404. The interactive client 404 provides a gaming interface that provides a list of available games that can be launched by a user within the context of the interactive client 404 and played with other users of the interactive system 400. The interactive system 400 also enables a particular user to invite other users to participate in playing a particular game by sending invitations to such other users from the interactive client 404. The interactive client 404 also supports audio, video, and text messaging (e.g., chatting) within the context of game play, provides leaderboards for games, and also supports the provision of in-game rewards (e.g., game coins and items).

[0159] The external resource system 730 provides an interface for the interactive client 404 to communicate with a remote server (e.g., a third-party server 412) to launch or access an external resource (i.e., an application or applet). Each third-party server 412 hosts, for example, an application or a small-scale version of an application based on a markup language (e.g., HTML5) (e.g., a game application, a utility application, a payment application, or a ride-sharing application). The interactive client 404 can launch a web-based resource (e.g., an application) by accessing an HTML5 file from a third-party server 412 associated with a web-based resource. The application hosted by the third-party server 412 is programmed in JavaScript using a software development kit (SDK) provided by the interactive server 422. The SDK includes an application programming interface (API) with functions that can be called or activated by a web-based application. The interactive server 422 hosts a JavasScript library that provides access to a given external resource to specific user data of the interactive client 404. HTML5 is an example of a technology for programming games, but applications and resources programmed based on other technologies can be used.

[0160] In order to integrate the functionality of the SDK into the web-based resource, the SDK is downloaded from the interactive server 422 by the third-party server 412, or the SDK is received by the third-party server 412 in other ways. Once downloaded or received, the SDK is included as part of the application code of the web-based external resource. The code of the web-based resource can then call or activate certain functions of the SDK to integrate the features of the interactive client 404 into the web-based resource.

[0161] The SDK stored on the interactive server system 410 effectively provides a bridge between external resources (e.g., applications 406 or applet) and the interactive client 404. This gives users a seamless experience of communicating with other users on the interactive client 404, while also retaining the look and feel of the interactive client 404. In order to bridge the communication between the external resources and the interactive client 404, the SDK facilitates the communication between the third-party server 412 and the interactive client 404. The WebViewJavaScriptBridge running on the computing system 402 establishes two one-way communication channels between the external resources and the interactive client 404. Messages are sent asynchronously between the external resources and the interactive client 404 via these communication channels. Each SDK function activation is sent as a message and a callback. Each SDK function is implemented by constructing a unique callback identifier and sending a message with the callback identifier.

[0162] By using the SDK, not all information from the interactive client 404 is shared with the third-party server 412. The SDK limits which information is shared based on the needs of the external resource. Each third-party server 412 provides an HTML5 file corresponding to a web-based external resource to the interactive server 422. The interactive server 422 can add a visual representation (e.g., a box design or other graphics) of the web-based external resource in the interactive client 404. Once the user selects the visual representation or instructs the interactive client 404 to access the features of the web-based external resource through the GUI of the interactive client 404, the interactive client 404 obtains the HTML5 file and instantiates the resource for accessing the features of the web-based external resource.

[0163] The interactive client 404 presents a graphical user interface (e.g., a login page or title screen) for an external resource. During, before, or after presenting the login page or title screen, the interactive client 404 determines whether the launched external resource has been previously authorized to access the user data of the interactive client 404. In response to determining that the launched external resource has been previously authorized to access the user data of the interactive client 404, the interactive client 404 presents another graphical user interface of the external resource including the functions and features of the external resource. In response to determining that the launched external resource has not been previously authorized to access the user data of the interactive client 404, after displaying the login page or title screen of the external resource for a threshold period of time (e.g., 3 seconds), the interactive client 404 slides up a menu (e.g., animating the menu to emerge from the bottom of the screen to the middle or other part of the screen) for authorizing the external resource to access the user data. The menu identifies the type of user data that the external resource will be authorized to use. In response to receiving a user selection of the accept option, the interactive client 404 adds the external resource to the list of authorized external resources and allows the external resource to access the user data from the interactive client 404. The external resource is authorized by the interactive client 404 to access the user data under the OAuth 2 framework.

[0164] The interaction client 404 controls the type of user data shared with the external resource based on the type of external resource that is authorized. For example, an external resource including a full-scale application (e.g., application 406) is provided with access to a first type of user data (e.g., a two-dimensional avatar of a user with or without different avatar characteristics). As another example, an external resource including a small-scale version of an application (e.g., a web-based version of the application) is provided with access to a second type of user data (e.g., payment information, a two-dimensional avatar of a user, a three-dimensional avatar of a user, and an avatar with various avatar characteristics). Avatar characteristics include different ways to customize the look and feel of an avatar (e.g., different poses, facial features, clothing, etc.).

[0165] The advertising system 732 operatively enables third parties to purchase advertisements for presentation to end users via the interactive client 404 and also handles the delivery and presentation of these advertisements.

[0166] Software Architecture

[0167] Figure 8800 is a block diagram illustrating a software architecture 802 that can be installed on any one or more of the devices described herein. The software architecture 802 is supported by hardware such as a machine 804, which includes a processor 806, a memory 808, and an I / O component 810. In this example, the software architecture 802 can be conceptualized as a stack of layers, where each layer provides specific functionality. The software architecture 802 includes layers such as an operating system 812, a library 814, a framework 816, and an application 818. In operation, the application 818 invokes an API call 820 through the software stack and receives a message 822 in response to the API call 820.

[0168] The operating system 812 manages hardware resources and provides public services. The operating system 812 includes, for example, a kernel 824, services 826, and drivers 828. The kernel 824 serves as an abstraction layer between the hardware and other software layers. For example, the kernel 824 provides memory management, processor management (e.g., scheduling), component management, networking and security settings, and other functions. Services 826 can provide other public services to other software layers. Drivers 828 are responsible for controlling or interfacing with the underlying hardware. For example, drivers 828 may include display drivers, camera drivers, or Low-power drivers, Flash drivers, Serial communication drivers (e.g., USB drivers), Drivers, audio drivers, power management drivers, etc.

[0169] The library 814 provides a common low-level infrastructure used by the application 818. The library 814 may include a system library 830 (e.g., a C standard library) that provides functions such as memory allocation functions, string manipulation functions, mathematical functions, etc. In addition, the library 814 may include an API library 832, such as a media library (e.g., a library for supporting the presentation and manipulation of various media formats, such as Moving Picture Experts Group-4 (MPEG4), Advanced Video Coding (H.264 or AVC), Moving Picture Experts Group Layer-3 (MP3), Advanced Audio Coding (AAC), Adaptive Multi-Rate (AMR) audio codec, Joint Photographic Experts Group (JPEG or JPG), or Portable Network Graphics (PNG)), a graphics library (e.g., an OpenGL framework for presenting in two dimensions (2D) and three dimensions (3D) in graphics content on a display), a database library (e.g., SQLite providing various relational database functions), a web library (e.g., WebKit providing web browsing functions), etc. The library 814 may also include various other libraries 834 to provide many other APIs to the application 818.

[0170] The framework 816 provides a common high-level infrastructure used by the applications 818. For example, the framework 816 provides various graphical user interface (GUI) functions, high-level resource management, and high-level positioning services. The framework 816 can provide a wide range of other APIs that can be used by the applications 818, some of which can be specific to a particular operating system or platform.

[0171] In an example, applications 818 may include a home application 836, a contact application 838, a browser application 840, a book reader application 842, a positioning application 844, a media application 846, a messaging application 848, a game application 850, and a variety of other applications such as third-party applications 852. Applications 818 are programs that execute functions defined in the program. Various programming languages ​​can be used to create one or more of the applications 818 constructed in various ways, such as object-oriented programming languages ​​(e.g., Objective-C, Java, or C++) or procedural programming languages ​​(e.g., C language or assembly language). In a specific example, third-party applications 852 (e.g., those created by entities other than the vendor of a particular platform using ANDROID TM or IOS TM Applications developed using a software development kit (SDK) can be mobile operating systems such as IOS TM ANDROID TM , Phone, or other mobile operating system running on the mobile software. In this example, the third-party application 852 can activate the API call 820 provided by the operating system 812 to facilitate the functions described in this article.

[0172] in conclusion

[0173] Changes and modifications may be made to the disclosed examples without departing from the scope of the present disclosure. These and other changes or modifications are intended to be included within the scope of the present disclosure as expressed in the following claims.

[0174] Glossary

[0175] "Carrier signal" refers to any intangible medium capable of storing, encoding or carrying instructions for execution by a machine and includes digital or analog communications signals or other intangible media to facilitate communication of such instructions. Instructions may be sent or received over a network using a transmission medium via a network interface device.

[0176] "Client Device" refers to any machine that interfaces with a communications network to obtain resources from one or more server systems or other client devices. A client device may be, but is not limited to, a mobile phone, a desktop computer, a laptop computer, a portable digital assistant (PDA), a smart phone, a tablet computer, an ultrabook, a netbook, a laptop computer, a multiprocessor system, a microprocessor-based or programmable consumer electronics product, a game console, a set-top box, or any other communications device that a user may use to access a network.

[0177] "Communications network" means one or more parts of a network, which may be an ad hoc network, an intranet, an extranet, a virtual private network (VPN), a local area network (LAN), a wireless LAN (WLAN), a wide area network (WAN), a wireless WAN (WWAN), a metropolitan area network (MAN), the Internet, a part of the Internet, a part of the public switched telephone network (PSTN), a plain old telephone service (POTS) network, a cellular telephone network, a wireless network, A network, other type of network, or a combination of two or more such networks. For example, the network or a portion of the network may include a wireless network or a cellular network, and the coupling may be a code division multiple access (CDMA) connection, a global system for mobile communications (GSM) connection, or other type of cellular or wireless coupling. In this example, the coupling may implement any of various types of data transmission technologies, such as single carrier radio transmission technology (1xRTT), evolution data optimized (EVDO) technology, general packet radio service (GPRS) technology, enhanced data rate for GSM evolution (EDGE) technology, the third generation partnership project (3GPP) including 3G, fourth generation wireless (4G) network, universal mobile telecommunications system (UMTS), high speed packet access (HSPA), world wide interoperability for microwave access (WiMAX), long term evolution (LTE) standards, other data transmission technologies defined by various standard setting organizations, other long distance protocols, or other data transmission technologies.

[0178] "Component" refers to a device, physical entity or logic with the following boundaries: the boundary is defined by a function or subroutine call, a branch point, an API or other technology provided for dividing or modularizing a specific processing or control function. Components can be combined with other components via their interfaces to perform machine processing. A component can be a packaged functional hardware unit designed for use with other components, and can be part of a program that generally performs a specific function in a related function. A component can constitute a software component (e.g., a code implemented on a machine-readable medium) or a hardware component. "Hardware component" is a tangible unit that can perform certain operations and can be configured or arranged in a certain physical manner. In various examples, one or more computer systems (e.g., an independent computer system, a client computer system or a server computer system) or one or more hardware components (e.g., a processor or a processor group) of a computer system can be configured by software (e.g., an application or an application part) to operate to perform certain operations as described herein. Hardware components can also be implemented mechanically, electronically, or in any suitable combination thereof. For example, a hardware component may include a dedicated circuit system or logic that is permanently configured to perform certain operations. The hardware component may be a dedicated processor, such as a field programmable gate array (FPGA) or an application specific integrated circuit (ASIC). The hardware component may also include a programmable logic or circuit system that is temporarily configured to perform certain operations by software. For example, the hardware component may include software executed by a general-purpose processor or other programmable processor. Once configured by such software, the hardware component becomes a specific machine (or a specific component of a machine), which is uniquely customized to perform the configured function and is no longer a general-purpose processor. It will be recognized that it can be determined for cost and time considerations whether to mechanically implement the hardware component in a dedicated and permanently configured circuit system or in a temporarily configured (e.g., configured by software) circuit system to implement the hardware component. Therefore, the phrase "hardware component" (or "hardware-implemented component") should be understood to include a tangible entity, that is, an entity that is physically constructed, permanently configured (e.g., hardwired) or temporarily configured (e.g., programmed) to operate in some way or perform certain operations described herein. Considering an example in which a hardware component is temporarily configured (e.g., programmed), it is not necessary to configure or instantiate each hardware component in the hardware component at any time. For example, where a hardware component includes a general purpose processor that is configured by software to become a special purpose processor, the general purpose processor may be configured as different special purpose processors (e.g., including different hardware components) at different times. The software configures one or more specific processors accordingly, such as to constitute a specific hardware component at one time and to constitute different hardware components at different times. Hardware components may provide information to other hardware components and receive information from other hardware components.Therefore, the described hardware components can be considered to be coupled in communication. In the case of multiple hardware components simultaneously, communication can be achieved by signal transmission between or among two or more hardware components in the hardware components (for example, by appropriate circuits and buses). In the example where multiple hardware components are configured or instantiated at different times, communication between such hardware components can be achieved, for example, by storing information in a memory structure accessible to multiple hardware components and retrieving information in the memory structure. For example, a hardware component can perform an operation and store the output of the operation in a memory device to which it is coupled in communication. Then, other hardware components can access the memory device at a subsequent time to retrieve the stored output and process it. The hardware component can also initiate communication with an input device or an output device, and can operate on resources (for example, a collection of information). The various operations of the example methods described herein can be performed at least in part by a temporary configuration (for example, by software) or one or more processors that are permanently configured to perform related operations. Whether it is a temporary configuration or a permanent configuration, such a processor can constitute a processor-implemented component that operates to perform one or more operations or functions described herein. As used herein, "processor-implemented components" refer to hardware components implemented using one or more processors. Similarly, the method described herein can be implemented at least in part by a processor, wherein one or more specific processors are examples of hardware. For example, at least some of the operation of the method can be performed by one or more processors or the parts implemented by the processor. In addition, one or more processors can also operate to support the execution of the related operations in the "cloud computing" environment or operate as "software as a service" (SaaS). For example, at least some of the operation can be performed by a group of computers (as an example of a machine including a processor), wherein these operations can be accessed via a network (for example, the Internet) and via one or more appropriate interfaces (for example, API). The execution of some operations in the operation can be distributed between processors, not only resident in a single machine, but deployed across multiple machines. In some examples, a processor or a part implemented by a processor can be located in a single geographic location (for example, in a home environment, an office environment or a server group). In other examples, a processor or a part implemented by a processor can be distributed across multiple geographic locations.

[0179] "Machine-readable storage media" refers to both machine storage media and transmission media. Therefore, these terms include both storage devices / media and carrier / modulated data signals. The terms "computer-readable medium," "machine-readable medium," and "device-readable medium" mean the same thing and may be used interchangeably in this disclosure.

[0180] “Machine storage media” refers to a single or multiple storage devices and media (e.g., centralized or distributed databases, and associated caches and servers) that store executable instructions, routines, and data. Thus, the term should be considered to include, but is not limited to, solid-state memory and optical and magnetic media, including memory internal or external to the processor. Specific examples of machine storage media, computer storage media, and device storage media include: non-volatile memory, including, for example, semiconductor memory devices such as erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), FPGA, and flash memory devices; magnetic disks, such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The terms “machine storage media,” “device storage media,” and “computer storage media” mean the same thing and may be used interchangeably in this disclosure. The terms “machine storage media,” “computer storage media,” and “device storage media” explicitly exclude carrier waves, modulated data signals, and other such media, at least some of which are encompassed by the term “signal media.”

[0181] “Non-transitory machine-readable storage medium” refers to a tangible medium capable of storing, encoding, or carrying instructions for execution by a machine.

[0182] "Signal medium" refers to any intangible medium that is capable of storing, encoding or carrying instructions to be executed by a machine, and includes digital or analog communication signals or other intangible media to facilitate the communication of software or data. The term "signal medium" should be deemed to include any form of modulated data signal, carrier wave, etc. The term "modulated data signal" means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. The terms "transmission medium" and "signal medium" mean the same thing and may be used interchangeably in this disclosure.

[0183] Changes and modifications may be made to the disclosed examples without departing from the scope of the present disclosure. These and other changes or modifications are intended to be included within the scope of the present disclosure as expressed in the following claims.

Claims

1. A machine comprising: one or more processors; as well as a memory storing instructions that, when executed by the one or more processors, cause the machine to perform operations comprising: providing, by an augmented reality (AR) system's AR application, a user interface to a user of the AR system; capturing, using one or more cameras of the AR system, video frame tracking data of gestures being performed by the user while the user is interacting with the AR user interface; generating skeletal 3D model data of the user's hand based on the video frame tracking data, the skeletal 3D model data comprising one or more skeletal 3D model features corresponding to identified visual landmarks of parts of the user's hand; Based on the skeleton 3D model data, generating target data identifying a virtual 3D object of the AR user interface; generating filtered target data based on the target data using a target filter component; and The filtered target data is provided to the AR application as a user input into the AR application.

2. The machine according to claim 1, wherein: The operations also include: generating target filter parameter data for the target filter component based on the video frame tracking data; and Wherein, the filtered target data is also generated based on the target data and the target filter parameter data.

3. The machine according to claim 2, wherein: The target filter component includes a low pass filter.

4. The machine according to claim 1, wherein: The operations also include: Generate filtered skeleton 3D model data by filtering the skeleton 3D model data using a skeleton 3D model filtering component; and The target data is generated based on the filtered skeletal 3D model data.

5. The machine according to claim 4, wherein: The instructions, when executed by the one or more processors, further cause the machine to perform operations comprising: Generating skeletal 3D model filter parameter data for the skeletal 3D model filtering component based on the video frame tracking data; and Wherein, the filtered target data is also generated based on the target data and the target filter parameter data.

6. The machine according to claim 5, wherein: The skeleton 3D model filtering component includes a low-pass filter.

7. The machine according to claim 1, wherein: The AR system includes a head wearable device.

8. A computer-implemented method comprising: Providing, by the one or more processors, a user interface for an AR application of the AR system; capturing, by the one or more processors, using one or more cameras of the AR system, video frame tracking data of gestures being performed by the user while the user is interacting with the AR user interface; generating, by the one or more processors, skeletal 3D model data of the user's hand based on the video frame tracking data, the skeletal 3D model data comprising one or more skeletal 3D model features corresponding to identified visual landmarks of portions of the user's hand; Generating, by the one or more processors, target data identifying a virtual 3D object of the AR user interface based on the skeletal 3D model data; generating, by the one or more processors, filtered target data from the target data using a target filter component; as well as The filtered target data is provided to the AR application by the one or more processors as user input into the AR application.

9. The computer-implemented method of claim 8, further comprising: generating, by the one or more processors, target filter parameter data for the target filter component based on the video frame tracking data; as well as Wherein, the filtered target data is also generated based on the target data and the target filter parameter data.

10. The computer-implemented method of claim 9, wherein: The target filter component includes a low pass filter.

11. The computer-implemented method of claim 8, further comprising: The one or more processors generate filtered skeleton 3D model data by filtering the skeleton 3D model data using a skeleton 3D model filtering component; as well as The target data is generated by the one or more processors based on the filtered skeletal 3D model data.

12. The computer-implemented method of claim 11 , further comprising: generating, by the one or more processors, skeletal 3D model filter parameter data for the skeletal 3D model filtering component based on the video frame tracking data; as well as Wherein, the filtered target data is also generated based on the target data and the target filter parameter data.

13. The computer-implemented method of claim 12, wherein: The skeleton 3D model filtering component includes a low-pass filter.

14. The computer-implemented method of claim 8, wherein: The AR system includes a head wearable device.

15. A non-transitory computer-readable storage medium comprising instructions that, when executed by a computer, cause the computer to perform operations comprising: Provide a user interface for the AR application of the AR system; capturing, using one or more cameras of the AR system, video frame tracking data of gestures being performed by the user while the user is interacting with the AR user interface; generating skeletal 3D model data of the user's hand based on the video frame tracking data, the skeletal 3D model data comprising one or more skeletal 3D model features corresponding to identified visual landmarks of parts of the user's hand; Based on the skeleton 3D model data, generating target data identifying a virtual 3D object of the AR user interface; generating filtered target data based on the target data using a target filter component; as well as The filtered target data is provided to the AR application as a user input into the AR application.

16. The computer-readable storage medium of claim 15, wherein: The operations also include: generating target filter parameter data for the target filter component based on the video frame tracking data; and Wherein, the filtered target data is also generated based on the target data and the target filter parameter data.

17. The computer-readable storage medium of claim 16, wherein: The target filter component includes a low pass filter.

18. The computer-readable storage medium of claim 15, wherein: The operations also include: Generate filtered skeleton 3D model data by filtering the skeleton 3D model data using a skeleton 3D model filtering component; and The target data is generated based on the filtered skeletal 3D model data.

19. The computer-readable storage medium of claim 18, wherein: The operations also include: Generating skeletal 3D model filter parameter data for the skeletal 3D model filtering component based on the video frame tracking data; and Wherein, the filtered target data is also generated based on the target data and the target filter parameter data.

20. The computer-readable storage medium of claim 15, wherein: The AR system includes a head wearable device.

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