Apparatus and method for identifying an object in an electronic device

Abstract

An electronic device is provided. The electronic device includes: a housing including a first plate, a second plate, and a side member, the side member surrounding a space between the first plate and the second plate; a display; an antenna array disposed in the housing or in a portion of the housing; an image sensor; a wireless communication device electrically coupled to the antenna array; a processor; and a memory. The memory may store instructions that, when executed, cause the processor to: obtain and receive at least one image using the image sensor, identify an object in the at least one image, send a series of directional beams along at least one second direction using the antenna array, receive a series of reflected waves reflected by the object using the antenna array, and identify the object based at least in part on the identified object and the series of reflected waves.

Description

Technical Field

[0001] The present disclosure generally relates to an apparatus and method for recognizing an object image in an electronic device, and more particularly, to an apparatus and method for recognizing an object image by combining outputs of a red, green, blue (RGB) camera module and a wireless communication module. Background Art

[0002] As the performance of electronic devices increases, various services and additional functions provided by the electronic devices are expanding. Various applications executable on the electronic devices are being developed to improve the practicality of the electronic devices and meet various needs of users.

[0003] Some of these applications are related to camera functions, and a user can capture his / her selfie or background using a camera module of an electronic device. For example, an electronic device can perform a recognition function based on an object image captured using a camera module. For example, an object can be a face or an iris.

[0004] The above information is presented as background information only to assist in understanding the present disclosure. No determination is made, and no assertion is made, as to whether any of the above content may be used as prior art with respect to the present disclosure. Summary of the invention

[0005] Solution to the problem

[0006] Facial recognition algorithms mainly used on electronic devices may use a method for utilizing an object image obtained on a red, green, and blue (RGB) camera, and a method for recognizing an object by combining an object image obtained on an RGB camera and depth information obtained on a depth camera. The method utilizing an object image obtained on an RGB camera may be susceptible to manipulation by a third party (e.g., a malicious spoofing attack using a photo or smartphone image). The method utilizing an RGB camera and a depth camera requires multiple camera modules at the electronic device.

[0007] Aspects of the present disclosure will at least solve the above-mentioned problems and / or disadvantages and provide at least the following advantages. Therefore, one aspect of the present disclosure is to provide an electronic device that can provide an apparatus and method for recognizing an object image by combining the outputs of an RGB camera module and a wireless communication module.

[0008] Another aspect of the present disclosure is to provide an electronic device that can provide an apparatus and method for setting a position to identify an object based at least in part on the object to be detected in an acquired object image, and sending a series of beams to the set position.

[0009] Another aspect of the present disclosure is to provide an electronic device that may provide an apparatus and method for identifying an object based on characteristics of a series of beams reflected by the identified object.

[0010] Additional aspects will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the presented embodiments.

[0011] According to one aspect of the present disclosure, an electronic device is provided. The electronic device includes: a housing, the housing including a first plate facing a first direction, a second plate facing away from the first plate, and a side member, the side member surrounding a space between the first plate and the second plate; a display, the display is seen through a first portion of the first plate; an antenna array, the antenna array is arranged in the housing or in a portion of the housing; an image sensor, the image sensor is seen through a second portion of the first plate and is arranged to face the first direction, the second portion of the first plate is close to the display; a wireless communication module, the wireless communication module is electrically coupled to the antenna array and is configured to form a directional beam using the antenna array; a processor, the processor is arranged in the housing and is operably coupled to the image sensor and the wireless communication module; and a memory, the memory is operably coupled to the processor. According to various embodiments, the memory may store instructions, which, when executed, enable the processor to: obtain and receive at least one image using the image sensor, detect an object in the at least one image, send a series of directional beams along at least one second direction using the antenna array, receive a series of reflected waves reflected by the detected object using the antenna array, and identify the detected object based on the series of reflected waves.

[0012] According to another aspect of the present disclosure, a method for identifying an object in an electronic device is provided. The method includes: obtaining at least one image using an image sensor; detecting an object in the at least one image; transmitting a series of one or more directional beams in the direction of the object using an antenna array provided in a housing or in a portion of the housing; receiving a series of reflected waves reflected by the detected object using the antenna array; and identifying the detected object based on the series of reflected waves.

[0013] According to another aspect of the present disclosure, a method for recognizing a face in an electronic device is provided. The method includes: obtaining at least one image using an image sensor; recognizing a facial image in the at least one image; setting a facial activity detection position and a facial recognition position based on the facial image; sending a series of first directional beams to the activity detection position; receiving a series of first reflected waves reflected at the activity detection position; detecting activity based on the received series of first reflected waves; sending a series of second directional beams to the facial recognition position; receiving a series of second reflected waves reflected at the facial recognition position, and recognizing the face based on the received series of second reflected waves.

[0014] Other aspects, advantages, and salient features of the disclosure will become apparent to those skilled in the art from the following detailed description, which, taken in conjunction with the accompanying drawings, discloses various embodiments of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The above and other aspects, features and advantages of certain embodiments of the present disclosure will become more apparent from the following description in conjunction with the accompanying drawings, in which:

[0016] Figure 1 is a block diagram of an electronic device in a network environment according to various embodiments of the present disclosure;

[0017] Figure 2 is a block diagram of a camera module according to an embodiment of the present disclosure;

[0018] Figure 3 is a block diagram of an electronic device according to an embodiment of the present disclosure;

[0019] Figure 4 is a diagram illustrating calculation of image data and coordinates of a subject obtained at an electronic device according to an embodiment of the present disclosure;

[0020] Figure 5 is a block diagram of an electronic device according to an embodiment of the present disclosure;

[0021] Figure 6 is a flow chart of an object recognition method of an electronic device according to an embodiment of the present disclosure;

[0022] Figure 7 is a flowchart of a method for recognizing a face in an electronic device according to an embodiment of the present disclosure; and

[0023] Figure 8 is a flowchart of a method for recognizing a face in an electronic device according to an embodiment of the present disclosure.

[0024] Throughout the drawings, like reference numerals will be understood to refer to like parts, components and structures. DETAILED DESCRIPTION

[0025] The following description with reference to the accompanying drawings is provided to assist in a comprehensive understanding of the various embodiments of the present disclosure as defined by the claims and their equivalents. It includes various specific details to assist in understanding, but these specific details are considered to be exemplary only. Therefore, it will be appreciated by those of ordinary skill in the art that various changes and modifications may be made to the various embodiments described herein without departing from the scope and spirit of the present disclosure. In addition, descriptions of well-known functions or configurations may be omitted for clarity and brevity.

[0026] The terms and words used in the following description and claims are not limited to the bibliographical meanings, but are merely used by the inventor to enable the present disclosure to be clearly and consistently understood. Therefore, it is apparent to those skilled in the art that the following description of various embodiments of the present disclosure is provided for illustrative purposes only and not for the purpose of limiting the present disclosure as defined by the appended claims and their equivalents.

[0027] It should be understood that the singular forms "a," "an," and "the" include plural references unless the context clearly dictates otherwise. Thus, for example, reference to "a component surface" includes reference to one or more of those surfaces.

[0028] Figure 1 is a block diagram illustrating electronic devices in a network environment according to various embodiments.

[0029] Reference Figure 1 , the electronic device 101 in the network environment 100 may communicate with the electronic device 102 via the first network 198 (e.g., a short-range wireless communication network), or communicate with the electronic device 104 or the server 108 via the second network 199 (e.g., a long-range wireless communication network). According to an embodiment, the electronic device 101 may communicate with the electronic device 104 via the server 108. According to an embodiment, the electronic device 101 may include a processor 120, a memory 130, an input device 150, a sound output device 155, a display device 160, an audio module 170, a sensor module 176, an interface 177, a haptic module 179, a camera module 180, a power management module 188, a battery 189, a communication module 190, a user identification module (SIM) 196, or an antenna module 197. In some embodiments, at least one of the components (e.g., the display device 160 or the camera module 180) may be omitted from the electronic device 101, or one or more other components may be added to the electronic device 101. In some embodiments, some of the components may be implemented as a single integrated circuit.For example, the sensor module 176 (eg, a fingerprint sensor, an iris sensor, or an illumination sensor) may be implemented to be embedded in the display device 160 (eg, a display).

[0030] The processor 120 may run, for example, software (e.g., program 140) to control at least one other component (e.g., hardware component or software component) of the electronic device 101 connected to the processor 120, and may perform various data processing or calculations. According to one embodiment, as at least part of the data processing or calculation, the processor 120 may load a command or data received from another component (e.g., sensor module 176 or communication module 190) into the volatile memory 132, process the command or data stored in the volatile memory 132, and store the resultant data in the non-volatile memory 134. According to an embodiment, the processor 120 may include a main processor 121 (e.g., a central processing unit (CPU) or an application processor (AP)) and an auxiliary processor 123 (e.g., a graphics processing unit (GPU), an image signal processor (ISP), a sensor hub processor, or a communication processor (CP)) that is independent of or combined with the main processor 121 in operation. Additionally or alternatively, the auxiliary processor 123 may be adapted to consume less power than the main processor 121, or adapted to be specifically used for a specified function. The auxiliary processor 123 may be implemented separately from the main processor 121 , or as part of the main processor 121 .

[0031] When the main processor 121 is in an inactive (e.g., sleep) state, the auxiliary processor 123 may control at least some of the functions or states related to at least one component (e.g., display device 160, sensor module 176, or communication module 190) among the components of the electronic device 101 (not the main processor 121), or when the main processor 121 is in an active state (e.g., running an application), the auxiliary processor 123 may control at least some of the functions or states related to at least one component (e.g., display device 160, sensor module 176, or communication module 190) among the components of the electronic device 101 together with the main processor 121. According to an embodiment, the auxiliary processor 123 (e.g., an image signal processor or a communication processor) may be implemented as part of another component (e.g., camera module 180 or communication module 190) that is functionally related to the auxiliary processor 123.

[0032] The memory 130 may store various data used by at least one component of the electronic device 101 (e.g., the processor 120 or the sensor module 176). The various data may include, for example, software (e.g., the program 140) and input data or output data for commands related thereto. The memory 130 may include a volatile memory 132 or a nonvolatile memory 134.

[0033] The program 140 may be stored as software in the memory 130 , and may include, for example, an operating system (OS) 142 , middleware 144 , or applications 146 .

[0034] The input device 150 may receive commands or data from outside the electronic device 101 (e.g., a user) to be used by other components of the electronic device 101 (e.g., the processor 120). The input device 150 may include, for example, a microphone, a mouse, a keyboard, or a digital pen (e.g., a stylus).

[0035] The sound output device 155 can output a sound signal to the outside of the electronic device 101. The sound output device 155 may include, for example, a speaker or a receiver. The speaker can be used for general purposes such as playing multimedia or playing records, and the receiver can be used for incoming calls. Depending on the embodiment, the receiver can be implemented as a separate part from the speaker, or as a part of the speaker.

[0036] The display device 160 may visually provide information to the outside of the electronic device 101 (e.g., a user). The display device 160 may include, for example, a display, a holographic device, or a projector, and a control circuit for controlling a corresponding one of the display, the holographic device, and the projector. According to an embodiment, the display device 160 may include a touch circuit adapted to detect a touch or a sensor circuit (e.g., a pressure sensor) adapted to measure the strength of a force caused by a touch.

[0037] The audio module 170 may convert sound into an electrical signal, or vice versa. According to an embodiment, the audio module 170 may obtain sound via the input device 150, or output sound via the sound output device 155 or an earphone of an external electronic device (e.g., electronic device 102) directly (e.g., wired) or wirelessly connected to the electronic device 101.

[0038] The sensor module 176 may detect an operating state (e.g., power or temperature) of the electronic device 101 or an environmental state (e.g., a state of a user) outside the electronic device 101, and then generate an electrical signal or data value corresponding to the detected state. According to an embodiment, the sensor module 176 may include, for example, a gesture sensor, a gyro sensor, an atmospheric pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an infrared (IR) sensor, a biometric sensor, a temperature sensor, a humidity sensor, or an illumination sensor.

[0039] The interface 177 may support one or more specific protocols to be used to connect the electronic device 101 directly (e.g., wired) or wirelessly to an external electronic device (e.g., the electronic device 102). According to an embodiment, the interface 177 may include, for example, a high-definition multimedia interface (HDMI), a universal serial bus (USB) interface, a secure digital (SD) card interface, or an audio interface.

[0040] The connection end 178 may include a connector, wherein the electronic device 101 can be physically connected to an external electronic device (e.g., the electronic device 102) via the connector. According to an embodiment, the connection end 178 may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

[0041] The haptic module 179 may convert the electrical signal into mechanical stimulation (eg, vibration or motion) or electrical stimulation that can be recognized by the user via his sense of touch or kinesthetic sense. According to an embodiment, the haptic module 179 may include, for example, a motor, a piezoelectric element, or an electrical stimulator.

[0042] The camera module 180 may capture still images or moving images. According to an embodiment, the camera module 180 may include one or more lenses, an image sensor, an image signal processor, or a flash.

[0043] The power management module 188 may manage power supply to the electronic device 101. According to an embodiment, the power management module 188 may be implemented as, for example, at least a part of a power management integrated circuit (PMIC).

[0044] The battery 189 may power at least one component of the electronic device 101. According to an embodiment, the battery 189 may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0045] The communication module 190 may support establishing a direct (e.g., wired) communication channel or a wireless communication channel between the electronic device 101 and an external electronic device (e.g., electronic device 102, electronic device 104, or server 108), and perform communication via the established communication channel. The communication module 190 may include one or more communication processors capable of operating independently from the processor 120 (e.g., an application processor (AP)) and supporting direct (e.g., wired) communication or wireless communication. According to an embodiment, the communication module 190 may include a wireless communication module 192 (e.g., a cellular communication module, a short-range wireless communication module, or a global navigation satellite system (GNSS) communication module) or a wired communication module 194 (e.g., a local area network (LAN) communication module or a power line communication (PLC) module). A corresponding one of these communication modules can communicate with an external electronic device via a first network 198 (e.g., a short-range communication network such as Bluetooth, Wireless Fidelity (Wi-Fi) Direct, or Infrared Data Association (IrDA)) or a second network 199 (e.g., a long-range communication network such as a cellular network, the Internet, or a computer network (e.g., a LAN or a wide area network (WAN))). These various types of communication modules can be implemented as a single component (e.g., a single chip), or these various types of communication modules can be implemented as multiple components separated from each other (e.g., multiple chips). The wireless communication module 192 can identify and authenticate the electronic device 101 in a communication network (such as the first network 198 or the second network 199) using user information (e.g., an International Mobile Subscriber Identity (IMSI)) stored in the user identification module 196.

[0046] The antenna module 197 may transmit or receive a signal or power to or from the outside of the electronic device 101 (e.g., an external electronic device). According to an embodiment, the antenna module 197 may include an antenna including a radiating element formed of a conductive material or a conductive pattern formed in or on a substrate (e.g., a PCB). According to an embodiment, the antenna module 197 may include a plurality of antennas. In this case, at least one antenna suitable for a communication scheme used in a communication network (such as the first network 198 or the second network 199) may be selected from the plurality of antennas by, for example, the communication module 190 (e.g., the wireless communication module 192). A signal or power may then be transmitted or received between the communication module 190 and the external electronic device via the selected at least one antenna. According to an embodiment, another component (e.g., a radio frequency integrated circuit (RFIC)) other than the radiating element may be additionally formed as a part of the antenna module 197.

[0047] At least some of the above components may be connected to each other via an inter-peripheral communication scheme (e.g., a bus, a general purpose input output (GPIO), a serial peripheral interface (SPI), or a mobile industry processor interface (MIPI)) and communicatively transmit signals (e.g., commands or data) therebetween.

[0048] According to an embodiment, a command or data may be sent or received between the electronic device 101 and the external electronic device 104 via the server 108 connected to the second network 199. Each of the electronic device 102 and the electronic device 104 may be a device of the same type as the electronic device 101, or a device of a different type from the electronic device 101. According to an embodiment, all or some operations to be executed in the electronic device 101 may be executed in one or more of the external electronic device 102, the external electronic device 104, or the server 108. For example, if the electronic device 101 should automatically execute a function or service or should execute a function or service in response to a request from a user or another device, the electronic device 101 may request the one or more external electronic devices to execute at least part of the function or service instead of executing the function or service, or the electronic device 101 may request the one or more external electronic devices to execute at least part of the function or service in addition to executing the function or service. The one or more external electronic devices that receive the request may execute the requested at least part of the function or service, or execute another function or another service related to the request, and transmit the result of the execution to the electronic device 101. The electronic device 101 may provide the result as at least a partial reply to the request with or without further processing the result. To this end, for example, cloud computing technology, distributed computing technology, or client-server computing technology may be used.

[0049] Figure 2 is a block diagram illustrating a camera module according to various embodiments.

[0050] Reference Figure 2, the camera module 180 may include a lens assembly 210, a flash 220, an image sensor 230, an image stabilizer 240, a memory 250 (e.g., a buffer memory), or an image signal processor 260. The lens assembly 210 may collect light emitted or reflected from an object whose image is to be captured. The lens assembly 210 may include one or more lenses. According to an embodiment, the camera module 180 may include a plurality of lens assemblies 210. In this case, the camera module 180 may form, for example, a dual camera, a 360-degree camera, or a spherical camera. Some of the plurality of lens assemblies 210 may have the same lens properties (e.g., viewing angle, focal length, autofocus, f-number, or optical zoom), or at least one lens assembly may have one or more lens properties different from those of another lens assembly. The lens assembly 210 may include, for example, a wide-angle lens or a telephoto lens.

[0051] The flash 220 may emit light, wherein the emitted light is used to enhance the light reflected from the object. According to an embodiment, the flash 220 may include one or more light emitting diodes (LEDs) (e.g., red, green, blue (RGB) LEDs, white LEDs, infrared (IR) LEDs, or ultraviolet (UV) LEDs) or xenon lamps. The image sensor 230 may acquire an image corresponding to the object by converting light emitted or reflected from the object and transmitted through the lens assembly 210 into an electrical signal. According to an embodiment, the image sensor 230 may include one image sensor selected from a plurality of image sensors having different properties (e.g., an RGB sensor, a black and white (BW) sensor, an IR sensor, or a UV sensor), a plurality of image sensors having the same properties, or a plurality of image sensors having different properties. Each image sensor included in the image sensor 230 may be implemented using, for example, a charge coupled device (CCD) sensor or a complementary metal oxide semiconductor (CMOS) sensor.

[0052] The image stabilizer 240 may move the image sensor 230 or at least one lens included in the lens assembly 210 in a specific direction, or control an operational property of the image sensor 230 (e.g., adjust the readout timing) in response to the movement of the camera module 180 or the electronic device 101 including the camera module 180. In this way, at least a portion of the negative effects (e.g., image blur) generated due to the movement of the image being captured is allowed to be compensated. According to an embodiment, the image stabilizer 240 may sense such movement of the camera module 180 or the electronic device 101 using a gyro sensor (not shown) or an acceleration sensor (not shown) arranged inside or outside the camera module 180. According to an embodiment, the image stabilizer 240 may be implemented as, for example, an optical image stabilizer.

[0053] The memory 250 may at least temporarily store at least a portion of an image acquired via the image sensor 230 for subsequent image processing tasks. For example, if multiple images are captured quickly or image capture is delayed due to shutter lag, the acquired original image (e.g., Bayer pattern image, high-resolution image) may be stored in the memory 250, and its corresponding copy image (e.g., low-resolution image) may be previewed via the display device 160. Then, if a specified condition is met (e.g., by a user's input or a system command), at least a portion of the original image stored in the memory 250 may be acquired and processed by, for example, the image signal processor 260. According to an embodiment, the memory 250 may be configured as at least a portion of the memory 130, or the memory 250 may be configured as a separate memory that operates independently of the memory 130.

[0054] The image signal processor 260 may perform one or more image processing on an image acquired via the image sensor 230 or an image stored in the memory 250. The one or more image processing may include, for example, depth map generation, three-dimensional (3D) modeling, panorama generation, feature point extraction, image synthesis, or image compensation (e.g., noise reduction, resolution adjustment, brightness adjustment, blurring, sharpening, or softening). Additionally or alternatively, the image signal processor 260 may perform control (e.g., exposure time control or readout timing control) on at least one of the components included in the camera module 180 (e.g., image sensor 230). The image processed by the image signal processor 260 may be stored back to the memory 250 for further processing, or the image may be provided to an external component outside the camera module 180 (e.g., memory 130, display device 160, electronic device 102, electronic device 104, or server 108). According to an embodiment, the image signal processor 260 may be configured as at least a part of the processor 120, or the image signal processor 260 may be configured as a separate processor that operates independently of the processor 120. If the image signal processor 260 is configured as a separate processor from the processor 120, at least one image processed by the image signal processor 260 may be displayed as it is by the processor 120 via the display device 160, or may be displayed after being further processed.

[0055] According to an embodiment, the electronic device 101 may include a plurality of camera modules 180 having different properties or functions. In this case, at least one camera module 180 of the plurality of camera modules 180 may form, for example, a wide-angle camera, and at least another camera module 180 of the plurality of camera modules 180 may form a telephoto camera. Similarly, at least one camera module 180 of the plurality of camera modules 180 may form, for example, a front camera, and at least another camera module 180 of the plurality of camera modules 180 may form a rear camera.

[0056] The electronic device according to various embodiments may be one of various types of electronic devices. The electronic device may include, for example, a portable communication device (e.g., a smart phone), a computer device, a portable multimedia device, a portable medical device, a camera, a wearable device, or a household appliance. According to an embodiment of the present disclosure, the electronic device is not limited to those electronic devices described above.

[0057] It should be understood that the various embodiments of the present disclosure and the terms used therein are not intended to limit the technical features set forth herein to specific embodiments, but include various changes, equivalent forms or alternative forms for corresponding embodiments. For the description of the accompanying drawings, similar reference numerals may be used to refer to similar or related elements. It will be understood that the nouns in the singular form corresponding to the term may include one or more things unless the relevant context clearly indicates otherwise. As used herein, each of the phrases such as "A or B", "at least one of A and B", "at least one of A or B", "A, B or C", "at least one of A, B and C" and "at least one of A, B or C" may include any one or all possible combinations of the items listed together with the corresponding one of the multiple phrases. As used herein, terms such as "1st" and "2nd" or "first" and "second" may be used to simply distinguish the corresponding component from another component, and do not limit the component in other aspects (e.g., importance or order). It will be understood that if an element (e.g., a first element) is referred to as being “combined with another element (e.g., the second element)”, “combined to another element (e.g., the second element)”, “connected with another element (e.g., the second element)”, or “connected to another element (e.g., the second element)” when the terms “operably” or “communicatively” are used or when the terms “operably” or “communicatively” are not used, it means that the element may be directly (e.g., wired) connected to the other element, wirelessly connected to the other element, or connected to the other element via a third element.

[0058] As used herein, the term "module" may include units implemented in hardware, software, or firmware, and may be used interchangeably with other terms (e.g., "logic," "logic block," "portion," or "circuit"). A module may be a single integrated component adapted to perform one or more functions or a minimum unit or portion of the single integrated component. For example, according to an embodiment, a module may be implemented in the form of an application specific integrated circuit (ASIC).

[0059] The various embodiments described herein may be implemented as software (e.g., program 140) including one or more instructions stored in a storage medium (e.g., internal memory 136 or external memory 138) that can be read by a machine (e.g., electronic device 101). For example, under the control of a processor, a processor (e.g., processor 120) of the machine (e.g., electronic device 101) may call at least one of the one or more instructions stored in the storage medium and execute the at least one instruction with or without the use of one or more other components. This enables the machine to operate to perform at least one function according to the at least one instruction called. The one or more instructions may include code generated by a compiler or code that can be run by an interpreter. A machine-readable storage medium may be provided in the form of a non-transitory storage medium. Among them, the term "non-transitory" only means that the storage medium is a tangible device and does not include a signal (e.g., an electromagnetic wave), but the term does not distinguish between data being semi-permanently stored in a storage medium and data being temporarily stored in a storage medium.

[0060] According to an embodiment, the method according to various embodiments of the present disclosure may be included and provided in a computer program product. The computer program product may be traded between a seller and a buyer as a product. The computer program product may be released in the form of a machine-readable storage medium (e.g., a compact disk read-only memory (CD-ROM)), or may be downloaded via an application store (e.g., Play Store TM ) The computer program product may be published (e.g., downloaded or uploaded) online, or the computer program product may be distributed (e.g., downloaded or uploaded) directly between two user devices (e.g., smart phones). If published online, at least part of the computer program product may be temporarily generated, or at least part of the computer program product may be at least temporarily stored in a machine-readable storage medium (such as a memory of a manufacturer's server, an application store's server, or a forwarding server).

[0061] According to various embodiments, each component (e.g., module or program) in the above-mentioned components may include a single entity or multiple entities. According to various embodiments, one or more components in the above-mentioned components may be omitted, or one or more other components may be added. Alternatively or additionally, multiple components (e.g., module or program) may be integrated into a single component. In this case, according to various embodiments, the integrated component may still perform the one or more functions of each component in the multiple components in the same or similar manner as a corresponding component in the multiple components before integration. According to various embodiments, the operations performed by a module, program or another component may be performed sequentially, in parallel, repeatedly or in a heuristic manner, or one or more operations in the operations may be run or omitted in different orders, or one or more other operations may be added.

[0062] Figure 3 is a block diagram of an electronic device according to an embodiment of the present disclosure.

[0063] Reference Figure 3 , the electronic device 101 may include a processor 300 , a memory 310 , a camera module 320 , a display 330 , an antenna array 340 , and a wireless communication module 350 .

[0064] The electronic device 101 may include a housing (not shown). The housing may include: a first plate facing the first direction; a second plate facing away from the first plate; and a side member surrounding a space between the first plate and the second plate.

[0065] Camera module 320 (eg, Figure 1 or Figure 2 The camera module 180 may include an image sensor (not shown, for example, Figure 2 The camera module 320 may be an image sensor 230 for generating pixel data by receiving visible light reflected by an object (e.g., a face, an iris, etc.). The camera module 320 may be viewed through the second portion of the first plate of the housing and may be disposed to face in a first direction, wherein the second portion of the first plate is proximate to the display 330.

[0066] Display 330 (eg, Figure 1 The display device 160 of the electronic device 101 can visually provide information (eg, an image captured by the camera module 320) to the outside of the electronic apparatus 101. The display 330 can be viewed through the first portion of the first plate of the housing.

[0067] The antenna array 340 may be disposed in the housing and / or in a portion of the housing. The antenna array 340 may transmit a series of directional beams along at least one second direction via a selected antenna array. The wireless communication module 350 may be electrically coupled to the antenna array 340 and may be configured to form a directional beam using the antenna array. For example, the wireless communication module 350 may be a millimeter wave wireless communication module and may be configured to transmit and / or receive at a frequency of 3 GHz to 100 GHz.

[0068] Memory 310 (eg, Figure 1 The memory 130 of the processor 300 may store various data used by the processor 300. The memory 310 may store software (e.g., Figure 1 140), and storing software for driving the learning engine to recognize an object image received from the camera module 320 (e.g., Figure 1 Procedure 140).

[0069] According to various embodiments, the memory 310 may store instructions for identifying an object image obtained by the camera module 320, sending a series of beams to a designated position of the identified object, receiving reflected waves of the series of beams reflected by the object, and identifying the object based at least in part on the identified object image and the received series of reflected waves. The instructions may cause the processor 300 to send a series of beams after identifying the object. The instructions may cause the processor 300 to determine the direction of sending a series of beams based at least in part on the identified object or a selected portion of the identified object. The instructions may identify the object by comparing the identified object and the contour detected by the series of reflected waves with a reference image and a reference contour. The instructions may cause the processor 300 to determine the distance between the object and the electronic device 101 based at least in part on the series of reflected waves. The instructions may cause the processor 300 to identify the object in the locked state of the electronic device 101, and if the object recognition is successful, the electronic device 101 is switched from the locked state to the unlocked state.

[0070] According to various embodiments, the memory 310 may store at least one template generated by learning. For example, the template may include at least one of a template for detecting the presence of an object, a template for detecting the activity of an object, and a template for identifying an object. According to various embodiments, the memory 310 may store location information about the presence, activity, and / or object recognition in the confirmed object image.

[0071] Processor 300 (eg, Figure 1The processor 120 of the electronic device 101 is disposed in the housing of the electronic device 101 and may be operably coupled to the camera module 320, the display 330, the wireless communication module 350, and the antenna array 340. The processor 300 may identify an object according to instructions stored in the memory 310. The processor 300 may obtain and receive at least one image through the camera module 320, and identify an object in the received image. The processor 300 may use the antenna array 340 to send a series of directional beams along at least one second direction, and receive a series of reflected waves reflected by the object. Based at least in part on the identified object and the series of reflected waves, the processor 300 may perform object recognition.

[0072] According to various embodiments, the wireless communication module 350 may be a millimeter wave device. The millimeter wave device may use beamforming to send a millimeter wave signal toward an object in a direction corresponding to a specific pixel of the image data, and may confirm the characteristics of the reflected signal by receiving a signal reflected by the object. In order to use the millimeter wave electronic device 101 in object recognition, it is necessary to select a necessary portion of the object and extract object information reflected by sending the millimeter wave toward the selected object portion. The electronic device 101 may enhance the security of object recognition by adding the unique signal characteristics of the millimeter wave device to object recognition. According to various embodiments, the electronic device 101 may shorten the millimeter wave image data creation time by optimizing the selection of the object portion (e.g., based on the specific position of the object of the image data) to perform beamforming at the millimeter wave device using the image data of the RGB camera, thereby reducing the total processing time of the object recognition system.

[0073] The electronic device 101 can perform recognition by obtaining an object (e.g., face) image to perform a setting function. The user can capture a face by driving the camera module 320. The processor 300 can obtain an image including a face from the camera module 320, and recognize the facial part in the obtained image. The processor 300 can extract features of the main part of the face from the recognized facial image. The main part of the face can be a part for detecting the presence of the face or the activity of the face or for identifying the face. The processor 300 can send millimeter waves by generating a series of beams along the direction corresponding to the extracted facial part using the wireless communication module 350 and the antenna array 340. The processor 300 can receive a series of beams reflected by the face using the wireless communication module 350 and the antenna array 340. The processor 300 can use deep learning, an artificial neural network, or a deep neural network to learn the information of the main part of the face. The memory 310 can store the information of the main part of the learned face. If reflected wave information of the main part of the face is received from the wireless communication module 350, the processor 300 can confirm the output of the deep learning system, which matches the features of the main part of the face stored in the memory 310 with the features based on the received reflected wave information, and confirm whether it corresponds to the user's face.

[0074] According to various embodiments, the electronic device 101 may use the machine learning engines for facial image recognition and reflected wave recognition as one machine learning engine. According to one embodiment, the electronic device 101 may use the machine learning engine for facial image recognition and the machine learning engine for reflected waves separately.

[0075] In one embodiment, the processor 300 may identify a facial part in the image data obtained at and received from the camera module 320, and set an identification position for identifying the face in the identified facial image. The processor 300 may use the antenna array 340 to perform beamforming and send millimeter waves to the identified position, receive the millimeter waves reflected by the face, and thereby identify whether it corresponds to the set user face. Facial recognition may be performed based on a deep learning algorithm.

[0076] In one embodiment, the processor 300 can identify facial parts in the image data acquired and received from the camera module 320, and set an activity detection position for detecting facial activity and a recognition position for recognizing the face in the recognized facial image. For example, the position can be a specific part, such as eyes, nose, lips, or a part that effectively represents the user's features. The specified position can be changed based on information of the image data (e.g., facial angle). For example, the activity detection position can be a specific part, such as eyes, nose, lips, for detecting the user's micro-movement. For example, the recognition position can be the entire facial area or the positions of the eyes, nose, and lips for specifying the user's face.

[0077] The processor 300 may detect the activity of the face by beamforming and sending millimeter waves to the activity detection position and receiving the millimeter waves reflected by the face. For example, the processor 300 may confirm whether it corresponds to the set user face by beamforming and sending millimeter waves to the recognition position and receiving the millimeter waves reflected by the face. Activity detection and facial recognition may be performed based on a deep learning algorithm.

[0078] In one embodiment, the processor 300 may recognize a face in the image data acquired and received from the camera module 320, and set a presence detection position for detecting the presence of the face, an activity detection position for detecting the activity of the face, and a recognition position for recognizing the face in the recognized facial image. The processor 300 may detect the presence of the face by beamforming and sending a millimeter wave to the set presence detection position and receiving the millimeter wave reflected by the face. The processor 300 may detect the activity of the face by beamforming and sending a millimeter wave to the set activity detection position and receiving the millimeter wave reflected by the face. The processor 300 may recognize whether it corresponds to the set user face by beamforming and sending a millimeter wave to the set recognition position and receiving the millimeter wave reflected by the face. According to one embodiment, presence and activity detection and facial recognition may be performed based on a deep learning algorithm.

[0079] According to various embodiments, the electronic device 101 may use a camera module 320 including an RGB camera, an antenna array 340, and a wireless communication module 350 to recognize a face. The electronic device 101 may perform facial detection and / or facial feature or facial landmark detection based on an image obtained from the camera module 320. The electronic device 101 may determine the direction of a series of beams based on facial feature information (one or more pixels in the image for beamforming), and the wireless communication module 350 may send a series of beams in the set direction via the antenna array 340. The wireless communication module 350 may receive a signal reflected by an object (face), forward the signal information to the processor 300, and recognize the face using the reflected signal and the information of the main part of the learned face stored in the memory 310.

[0080] According to various embodiments, if a facial recognition application is executed, the electronic device 101 may display a guide message notifying the execution of facial recognition. For example, in order to obtain a high-quality image, the electronic device 101 may use the display 330 and / or a speaker (not shown) to guide the camera module 320 to take a photo at a specific distance.

[0081] According to various embodiments, the electronic device 101 may obtain and receive an image using the camera module 320, and confirm pixels corresponding to facial parts in the received image. The processor 300 may confirm pixels of parts for facial landmarks in the confirmed facial image. Facial landmarks may be eyes, noses, and / or lips. If necessary, the electronic device 101 may confirm various types of landmarks. For example, the electronic device 101 may confirm in a facial image a landmark for detecting the presence of a face (e.g., a central pixel position of a facial image), a landmark for detecting facial activity (e.g., a specific position of a face for detecting movement of eyes, noses, or lips), and a position for identifying a face (e.g., an entire area or portion of a face (e.g., a collection of multiple landmarks including eyes, noses, and lips)).

[0082] According to various embodiments, the electronic device 101 may select pixels corresponding to the recognized facial image or pixels for portions of facial landmarks, and beamform the selected pixels using the wireless communication module 350 and the antenna array 340. The electronic device 101 may send a series of beams in a set direction, and receive signals reflected by an object (e.g., a face) through the wireless communication module 350 and the antenna array 340. According to one embodiment, the wireless communication module 350 and the antenna array 340 may be millimeter wave devices, and may generate millimeter wave image data of a corresponding portion by sending and receiving a series of beams in the direction of the selected pixels in the facial image. For example, the electronic device 101 may use the millimeter wave image data to detect the activity of the facial image, thereby utilizing it in facial recognition.

[0083] If beamforming is performed to generate millimeter wave image data for selected pixels, the electronic device 101 may set azimuth and elevation values ​​to generally set the beamforming direction.

[0084] Figure 4 is a diagram illustrating calculation of image data obtained at the electronic device 101 and coordinates of a subject according to an embodiment of the present disclosure.

[0085] Reference Figure 4 , the electronic device 101 may perform facial recognition by capturing the subject 410. The electronic device 101 may obtain an image 440 of the subject 410 using the camera module 320, confirm a facial region 445 by recognizing the obtained image 440, and confirm a center coordinate 443 of the facial region 445. The size of the actual captured region 420 of the subject 410 and the image 440 obtained by the electronic device 101 may be different. Therefore, the center coordinate 425 of the facial image 423 captured from the subject 410 and the center coordinate 443 of the facial region 445 of the image 440 obtained at the electronic device 101 may be different.

[0086] Based on the image of the facial region 445 of the obtained image 440, the electronic device 101 can send a series of beams to the subject 410. For example, the electronic device 101 can detect a landmark in the facial region 445 and determine the direction of the series of beams based on the pixel information of the detected landmark. Based on the center coordinates 443 (e.g., pixel position) of the image (e.g., facial region 445) obtained by the camera module 320, the electronic device 101 can estimate to match the facial center coordinates 425 of the actual subject 410.

[0087] If a specific distance is maintained between the subject 410 and the electronic device 101, the electronic device 101 can obtain a high-quality image. For example, if a facial recognition application is run, the electronic device 101 can use a guidance message to guide the effective distance of facial recognition. For example, based on the distance between the subject 410 and the electronic device 101 being 20 cm, the effective distance of facial recognition can be ±4 cm. The electronic device 101 can pre-calculate the horizontal scale A and the vertical scale B based on the camera scale at a distance of 20 cm. Therefore, the center coordinates of the actual subject's face can be inferred based on Formula 1.

[0088]

[0089] By using the coordinates (pixel positions) of the landmark portion in the image (e.g., the face region 445) in the same manner as in Equation 1, the coordinates of the portion corresponding to the actual subject can be inferred. The RF position of the millimeter wave device can be preset as (xmmWave ,y mmWave ), and is stored in the memory 310. For example, it can be assumed that all coordinates of the image obtained at the camera module 320 are based on mm. Therefore, if the subject is 20 cm away from the electronic device 101, the three-dimensional coordinates of the RF of the millimeter wave device may be (0, x mmWave ,y mmWave ), and the three-dimensional center coordinates of the face of the actual subject may be (200, x', y'). In this way, the azimuth and elevation angles of the beamforming of the millimeter wave device may be estimated based on Equation 2.

[0090]

[0091]

[0092] If the millimeter wave image data for the selected pixels of the facial image is obtained using the wireless communication module 350, the electronic device 101 can perform facial recognition using the obtained millimeter wave image. Facial recognition may further include presence detection and / or activity detection. Using the wireless communication module 350 and the antenna array 340, the electronic device 101 may send a series of beams for detecting presence and / or activity and a series of beams for facial recognition to the subject.

[0093] According to one embodiment, the signal reflected by the subject may include information based on the movement and facial curve of the subject. For example, the movement of the subject may continuously cause the phase and / or time of flight (TOF) value of the reflected wave of the electronic device 101 to fluctuate. The facial curve of the subject may be different for each person, and the phase and / or TOF value of the signal reflected by the face of the subject may be different values ​​according to each person. In addition, according to the frequency of the wave reflected by the human skin, the amplitude reduction pattern may represent a unique feature that is different from other objects. The electronic device 101 can learn the image of the corresponding user and the reflected wave information (e.g., phase, TOF, amplitude, etc.) according to the user (e.g., the user who has registered the image for facial recognition on the electronic device 101), and store it in the memory 310.

[0094] According to various embodiments, the electronic device 101 may store learned information (templates) for facial presence detection, activity detection, and facial recognition in the memory 310. The learned information for facial recognition may be generated using deep learning, a deep neural network, or an artificial neural network that may be performed on the electronic device 101 or an external server. For example, deep learning may employ a convolutional neural network (CNN) scheme. Learning using CNN may be performed by inputting the facial information of the user to be learned into the CNN, and extracting and storing features as templates based on the learned results.

[0095] For example, the method for obtaining learning information can input the image information of a specific part and the received information of the wireless communication module 350 for each specific part (for example, the phase, TOF, amplitude obtained from the reflected wave of the 60GHz beam) into the CNN, and the specific part can be the facial landmarks of the eyes, nose and lips obtained from at least one actual user face image, and calculate the corresponding output value to be true, and then input the same parameters of the ordinary user and calculate the corresponding output value to be false. The learning method using CNN can repeat such calculations for a set number of times, update (update in the back propagation method) the errors that occur in the calculation, generate a model (template) that makes the user parameters true and store it in the memory. The template may include an existence template, an activity template and a facial recognition template. The existence template and the activity template can be used for all users, and the facial recognition template can be a unique template generated when training user images and reflected waves.

[0096] This approach can pre-configure the template with parameters of common users and train the template with a transfer learning method that fine-tunes it with parameter values ​​of new users.

[0097] The electronic device 101 can perform facial recognition by comparing the image information and reflected waves received when executing the facial recognition application with the corresponding information stored in the memory. When using the trained model for recognition, the electronic device 101 can perform recognition by inputting parameter values ​​based on the image and reflected waves received in real time as inputs to the CNN. If the output of the CNN is true, the electronic device 101 can be determined as an authorized user, and if the output of the CNN is false, it is determined as an unauthorized user.

[0098] Figure 5 is a block diagram of an electronic device according to an embodiment of the present disclosure. Figure 5 An example is shown in which the electronic device 101 detects activity of an image obtained through the camera module 180 and recognizes a face based on the detected activity.

[0099] Reference Figure 5 , electronic devices (e.g. Figure 1 The electronic device 101 may include a face detection module 510, a position detection module 520, an activity positioning module 530, an activity detection module 540, an identification positioning module 550 and a face recognition module 560. Figure 5 The electronic device 101 may be configured as a processor (eg, Figure 1 processor 120, Figure 3 Configuration of the processor 300).

[0100] The face detection module 510 can detect the face from the camera module (e.g. Figure 1 Camera module 180, Figure 2 and Figure 3 The face detection module 510 may detect a facial image in the obtained image. For example, in order to detect faces of various sizes, the face detection module 510 may generate a pyramid image from the obtained image and use a classifier (e.g., adaptive boost (AdaBoost)) to determine whether a region of a specific size is a face when moving pixel by pixel.

[0101] The position detection module 520 may detect facial features or facial landmarks in the detected facial image. According to various embodiments, the position detection module 520 may specify eyes, nose, and lips, and specify a facial region. For example, the position detection module 520 may detect a position for detecting the presence of a face in a facial image (e.g., the center of the image), a position for detecting facial activity (e.g., a specific position of the face for detecting eyes, nose, and eye movement), and a position for recognizing a face (e.g., the entire facial region, or the positions of eyes, nose, and lips for detecting facial features).

[0102] The activity positioning module 530 may select a facial position (e.g., a specific pixel position of a facial image) for detecting facial activity, and beamform the beams through the wireless communication module 350 and the antenna array 340 to send a series of beams to the selected facial position. The wireless communication module 350 and the antenna array 340 may send a series of beams in corresponding directions based on the activity beamforming information (e.g., azimuth and elevation) set at the activity positioning module 530, and receive signals reflected by the subject.

[0103] The activity detection module 540 can detect facial activity based on the signal reflected by the subject and received at the antenna array 340. The activity detection module 540 can calculate the TOF, phase and / or amplitude of the received reflected signal, and detect activity based on the activity template storing the calculated information in the memory 310. The recognition and positioning module 550 can select a facial position (e.g., the entire facial image area or a set of landmarks including multiple landmarks) for recognizing a face, and form a beam to send a series of beams to the selected position. The wireless communication module 350 and the antenna array 340 can send a series of beams along corresponding directions based on the beamforming information (e.g., azimuth and elevation) for facial recognition set at the recognition and positioning module 550, and receive the signal reflected by the subject.

[0104] The facial recognition module 560 can recognize a facial image based on a signal reflected by the subject and received at the antenna array 340. The facial recognition module 560 can calculate the TOF, phase and / or amplitude of the received reflected signal, and recognize the facial image of the user based on the facial recognition template storing the calculated information in the memory 310. The activity positioning module 530 can be positioned to measure the micro-movement of the object, and the activity detection position can be used to measure the distance to the object. For example, the activity detection position can be a facial area or a part of a facial area. The facial recognition module 560 can perform facial recognition based on object information (e.g., distance information from the object, TOF) using deep learning information.

[0105] According to various embodiments, the electronic device 101 may detect the activity of a facial image obtained using a millimeter wave device, and if activity is detected, the facial image is recognized. For example, even if a person's face is motionless, micrometer-level movement may occur continuously. Such movement may cause the phase or TOF value to fluctuate continuously relative to the reflected wave of the millimeter wave device. The electronic device 101 may use deep learning (or machine learning) to pre-store such movement characteristics in a memory in a specific pattern. Depending on the frequency, the reflected wave from the human skin may exhibit characteristics different from other objects in the amplitude reduction pattern of the reflected wave. The electronic device 101 may also pre-store the amplitude reduction pattern of the reflected wave in the memory. The activity positioning module 530 may perform beamforming to send a series of beams to a position for detecting activity (e.g., the eye, nose, or lip position of the facial image) and receive a signal reflected by the face of the subject. The activity detection module 540 may detect activity by comparing the phase or TOF pattern of the millimeter wave image data with the micro-motion pattern of the trained face stored in the memory, or by comparing the amplitude reduction pattern based on the frequency of the reflected wave with the pre-stored human skin pattern.

[0106] According to various embodiments, if the electronic device 101 detects activity (for example, if the characteristics of the reflected wave are similar to the reflected wave pattern of a person's face, the condition for activity detection is met), the recognition and positioning module 550 can perform additional beamforming toward the facial position (facial area or a part of the face including multiple landmarks in the facial area) for facial recognition. The electronic device 101 can send a series of beams to the facial position of the subject for additional facial recognition, and receive signals reflected by the corresponding facial position of the subject. The facial recognition module 560 can recognize the user's face based on the recognized facial image, a series of reflected waves, and a facial recognition template stored in the memory.

[0107] In doing so, if the millimeter wave image data for detecting activity is sufficient not only to detect activity but also to recognize a face, the electronic device 101 may not perform additional beamforming. Figure 5 The identification and positioning module 550 can be omitted.

[0108] In various embodiments, if beamforming for facial activity detection and beamforming for facial recognition are used separately, the electronic device 101 may perform beamforming for activity detection on a specific part of the face, and if the specific part of the face is matched, calculate the direction of other areas based on the corresponding beam direction. If the beamforming direction of the millimeter wave device is determined from pixel information of a facial image obtained at a camera, the electronic device 101 may cause a beamforming error depending on the installation position of the camera module and the millimeter wave device or the distance between the user and the electronic device 101. Therefore, beamforming for activity detection can be used to locate the user's face and measure the distance between the electronic device 101 and the face by repeatedly performing beamforming on a specific area.

[0109] According to various embodiments, if millimeter wave image data is generated, the electronic device 101 can compare the data (template) generated by the training through feature extraction of a deep learning (e.g., CNN) algorithm, and determine the success or failure of facial recognition by calculating a matching score according to a predetermined algorithm. Whether facial recognition is successful or failed, the electronic device 101 can use a pre-stored template for the face as additional data for continuous updating according to conditions. According to various embodiments, the electronic device 101 may include: a housing, the housing including a first plate facing a first direction, a second plate facing away from the first plate, and a side member surrounding the space between the first plate and the second plate; a display 330, which is seen through a first portion of the first plate; an antenna array 340, which is disposed in the housing and / or in a portion of the housing; an image sensor 230, which is seen through a second portion of the first plate and is disposed to face the first direction, and the second portion of the first plate is close to the display; a processor 300, which is disposed in the housing and is operably coupled to the image sensor and the wireless communication device; a memory 310, which is operably coupled to the processor. The memory 310 may store instructions which, when executed, cause the processor 300 to: obtain and receive at least one image using the image sensor 230, identify an object in the image, send a series of directional beams along at least one second direction using the antenna array 340, receive a series of reflected waves reflected by the object using the antenna array 340, and identify the object based at least in part on the identified object and the series of reflected waves.

[0110] According to various embodiments, the wireless communication module 350 may be configured to transmit and / or receive at a frequency of 3 GHz to 100 GHz.

[0111] According to various embodiments, the instructions may cause the processor 300 to send a series of beams after identifying an object.

[0112] According to various embodiments, the object may include a face of a user.

[0113] According to various embodiments, the second direction may be the same as the first direction.

[0114] According to various embodiments, the instructions may cause the processor 300 to determine the second direction based at least in part on the identified object or a selected portion of the identified object.

[0115] According to various embodiments, the memory 310 may store a reference image and a reference profile of an object based on a user, and the instruction may perform recognition by comparing the recognized object and the profile detected by a series of reflected waves with the reference image and the reference profile.

[0116] According to various embodiments, the instructions may cause the processor 300 to determine a distance between an object and the electronic device based at least in part on the series of reflected waves.

[0117] According to various embodiments, the instructions may enable the processor 300 to perform recognition when the electronic device 101 is locked, and if the recognition is successful, switch the locked state of the electronic device 101 to an unlocked state.

[0118] Figure 6 is a flowchart of an object recognition method of an electronic device according to an embodiment of the present disclosure.

[0119] Reference Figure 6 , the electronic device 101 may perform object recognition based on the object image and the millimeter wave according to the signal reflected by the object. In operation 611, the electronic device 101 may use a camera module (eg, Figure 1 Camera module 180, Figure 2 and Figure 3 In operation 613, the electronic device 101 may identify an intended object region and a main portion of the object in the obtained object image, and detect a marker for identifying the object in the identified object image.

[0120] In operation 615, the electronic device 101 may use a wireless communication module (eg, Figure 3The wireless communication module 350 and the antenna array 340 of the electronic device 101 can send a series of directional beams based on the detected object markers. The electronic device 101 can form a beam in the direction of the object position corresponding to the detected marker in the identified object image, and the wireless communication module and the antenna array can send a series of beams to the marker position of the object. In operation 617, the electronic device 101 can receive a series of reflected waves reflected by the subject. In operation 619, the electronic device 101 can perform object recognition based on the identified object image and the received series of reflected waves. For example, object recognition can be performed by comparing the identified object and the contour detected by the series of reflected waves with the reference image and the reference contour.

[0121] According to various embodiments, the object may be a person's face. The wireless communication module 350 and the antenna array 340 may be millimeter wave devices. The millimeter wave device may use beamforming to send a signal to a specific location of the object, and the processor 300 may confirm the characteristics of the signal reflected by the object through the wireless communication module 350. For example, if a millimeter wave device is used to recognize a face, the generation time of the image data may be shortened by confirming information of necessary parts of the face (e.g., the eyes, nose, and lips of the face) and sending a signal to the confirmed location using beamforming. For example, the electronic device 101 may detect facial activity in facial recognition by sending a series of directional beams to specific locations of the face (e.g., eyes, nose, and / or lips), and if activity is detected, the face is recognized by sending a series of directional beams to the facial area of ​​the image.

[0122] Figure 7 is a flowchart of a method for recognizing a face in an electronic device according to various embodiments of the present disclosure. Figure 7 A flowchart is shown in which the electronic device 101 performs the following operations: calculating the azimuth and elevation of the beamforming of the millimeter wave device for each pixel of the facial image, forming a beam based on the calculation result, and performing activity detection and facial recognition based on the signal reflected by the subject according to the beamforming.

[0123] Reference Figure 7 , electronic devices (e.g. Figure 1 The electronic device 101 may perform facial recognition based on the facial image and the millimeter wave according to the signal reflected by the object, and perform millimeter wave imaging based on the signal reflected by the face. In operation 711, the electronic device 101 may perform facial recognition based on the facial image and the millimeter wave according to the signal reflected by the face. Figure 1 Camera module 180, Figure 2 and Figure 3The electronic device 101 may obtain an image including a face by using a camera module 320. In operation 713, the electronic device 101 may identify a facial region and a main part of the face in the obtained image. In operation 715, the electronic device 101 may detect a landmark for facial recognition in the recognized facial image. The electronic device 101 may calculate the coordinates of the facial region in the image obtained by the camera module or the position (e.g., pixel coordinates) of a part that may be a landmark of the face. The electronic device 101 may select a position for detecting facial activity and a position for recognizing the face. For example, the position for detecting facial activity may select the pixel coordinates of a specific part, which may be a landmark of the eyes, nose, and lips in the facial image, and the position for recognizing the face may select a set of pixel coordinates collected from the entire facial image within a limited time.

[0124] In operation 717, the electronic device 101 may calculate the azimuth and elevation of the position of the facial image for facial activity detection. For example, the electronic device 101 may calculate the azimuth and elevation of the beam for activity detection by applying the activity detection position information to Equations 1 and 2. In operation 719, the electronic device 101 may send a series of beams to the activity detection position of the subject based on the calculated azimuth and elevation. In operation 721, the electronic device 101 may receive a series of reflected waves of the beam reflected by the subject. In operation 723, the electronic device 101 may calculate the phase, TOF, and amplitude values ​​from the received reflected waves, and detect facial activity based on the calculated values. According to one embodiment, the memory (e.g., Figure 3 The memory 310 of the electronic device 101 may store an activity template for detecting facial activity. For example, the activity template may be a specific pattern that uses deep learning to train the phase, TOF, and amplitude changes of the millimeter wave device based on the micro-movement (vibration) of the face. The electronic device 101 may confirm the matching score by matching the phase, TOF, and / or amplitude values ​​of the reflected wave received at the millimeter wave device with the trained activity template, and detect facial activity based on the confirmed matching score. If facial activity is not detected (determined to be false), the electronic device 101 may determine that facial recognition has failed and complete the recognition.

[0125] If facial activity is detected (determined to be true), in operation 725, the electronic device 101 may confirm whether there is additional position information for facial recognition (position information for facial recognition (pixel coordinates)). For example, the memory may store an activity template and a facial recognition template, and in operation 715, the electronic device 101 may determine a flag for activity detection and facial recognition. In operation 725, the electronic device 101 may calculate the azimuth and elevation of a specified position of a facial image for facial recognition. For example, the electronic device 101 may calculate the azimuth and elevation of a beam for facial recognition by applying facial recognition position information to Equations 1 and 2. In operation 727, the electronic device 101 may send a series of beams to the facial recognition position of the subject based on the calculated azimuth and elevation. In operation 729, the electronic device 101 may receive a series of reflected waves of the beam reflected by the subject. In operation 731 , the electronic device 101 may calculate phase, TOF, and amplitude values ​​from the received reflected wave, and perform facial recognition by matching the calculated values ​​with a facial recognition template.

[0126] Figure 8 is a flowchart of a method for recognizing a face in an electronic device according to an embodiment of the present disclosure.

[0127] Reference Figure 8 , the electronic device 101 may perform facial recognition based on the facial image, and perform millimeter wave imaging based on the signal reflected by the face. In operation 811, the electronic device 101 may perform facial recognition based on the facial image, and perform millimeter wave imaging based on the signal reflected by the face. Figure 1 Camera module 180, Figure 2 and Figure 3 The electronic device 101 may obtain an image including a face by using a camera module 320. In operation 813, the electronic device 101 may identify a facial region and a main part of a face in the obtained image. In operation 815, the electronic device 101 may detect a mark for facial recognition in the recognized facial image. The electronic device 101 may calculate the coordinates of the facial region in the image obtained by the camera module or the position (e.g., pixel coordinates) of the part that may be a facial mark. In operation 815, the electronic device 101 may distinguish and select a set of positions for existence detection, positions for facial activity detection, and / or positions for facial recognition. For example, the number of groups (pixel coordinates) may increase in the order of positions for existence detection, positions for facial activity detection, and positions for facial recognition. For example, the position for existence detection may use the center coordinates of the recognized facial image, the position for facial activity detection may select a specific part, which may be the facial marks of the eyes, nose, and lips in the facial image, and the position for facial recognition may select a set of all coordinates collected from the entire facial image within a limited time.

[0128] In operation 817, the electronic device 101 may calculate the azimuth and elevation of the corresponding beam for the location of the presence detection by applying equations 1 and 2. In operation 819, the electronic device 101 may send a series of directional beams to the subject by forming beams based on the calculated azimuth and elevation. In operation 821, the electronic device 101 may receive reflected waves of a series of beams reflected by the subject, and confirm whether the subject exists within a distance range set based on the phase and / or TOF value of the received reflected waves. In doing so, if the distance between the subject and the assumed subject is closer or farther (e.g., 20 cm), the electronic device 101 may recalculate the scales A and B. If there is no subject within the set distance range in the reflected wave information, the electronic device 101 may recognize the facial image in operation 811 and recalculate the coordinates of the facial area in the recognized facial image.

[0129] If the presence of a face is detected, the electronic device 101 may detect facial activity in operation 850. Figure 7 Operation 850 of detecting activity is performed in the same manner as operations 717 to 723 of the electronic device 101. If facial activity is detected, in operation 870, the electronic device 101 may perform facial recognition. Figure 7 Operation 870 of recognizing a face is performed in the same manner as operations 725 to 731 .

[0130] According to various embodiments, a method for identifying an object in an electronic device 101 may include: obtaining at least one image using an image sensor; identifying an object in the image; sending a series of one or more directional beams in the direction of the object using an antenna array disposed in a shell or a portion of the shell; receiving a series of reflected waves reflected by the object using the antenna array; and identifying the object at least in part based on the identified object and the series of reflected waves.

[0131] According to various embodiments, a series of directional beams may be transmitted at frequencies between 3 GHz and 100 GHz.

[0132] According to various embodiments, the object may include a face of a user.

[0133] According to various embodiments, transmitting the series of directional beams may further include determining a direction of the series of beams based at least in part on the identified object or a selected portion of the identified object.

[0134] According to various embodiments, the object recognition method of the electronic device 101 may store reference images and reference contours of objects based on users. Recognizing an object may be performed by comparing the recognized object and the contour detected by a series of reflected waves with the reference images and reference contours.

[0135] According to various embodiments, the object recognition method of the electronic device 101 may further include performing recognition when the electronic device is locked, and if the recognition is successful, switching the locked state of the electronic device to an unlocked state.

[0136] According to various embodiments, a method for recognizing a face in an electronic device may include: obtaining at least one image using an image sensor, recognizing a facial image in the image, setting a facial activity detection position and a facial recognition position based on the facial image, sending a series of first directional beams to the activity detection position, receiving a series of first reflected waves reflected at the activity detection position, detecting activity based on the received series of first reflected waves, sending a series of second directional beams to the facial recognition position, receiving a series of second reflected waves reflected at the facial recognition position, and recognizing the face based on the received series of second reflected waves.

[0137] According to various embodiments, setting the activity detection position may set the coordinates of pixels based on at least one feature of the eyes, nose, and lips of the face as the activity detection position. Setting the facial recognition position may set the coordinates of pixels based on a facial part or a portion of a facial part as the facial recognition position.

[0138] According to various embodiments, detecting activity may include setting a series of first directional beams by calculating the azimuth and elevation of the activity detection location, sending a series of first directional beams, receiving a series of beams reflected from the face, calculating the TOF of the reflected waves based on the received series of reflected waves, and detecting activity based on the TOF of the reflected waves and a stored trained activity template.

[0139] According to various embodiments, recognizing a face may include setting a series of second directional beams by calculating the azimuth and elevation of the facial recognition location, sending a series of second directional beams, receiving a series of beams reflected by the face, calculating the TOF of the reflected waves based on the received series of reflected waves, and recognizing the face based on the TOF of the reflected waves and a stored facial recognition template.

[0140] According to various embodiments, the object recognition method of the electronic device may further include detecting the presence of a face. Detecting the presence may include setting the pixel coordinates of the center position of the face as the presence detection position, setting the direction of a series of beams by calculating the azimuth and elevation of the presence detection position, transmitting the set series of directional beams, receiving a series of beams reflected by the face, calculating the TOF of the reflected waves based on the received series of reflected waves, and detecting the presence based on the TOF of the reflected waves and the stored presence template.

[0141] The electronic device according to various embodiments may perform object recognition using a wireless communication function in object recognition. The electronic device may use a wireless communication device to detect the activity of an object image obtained at a camera, identify the detected active object image, and thereby prevent malicious recognition attempts (e.g., spoofing attacks). In addition, the electronic device may use the object image obtained at the camera to select beamforming pixels of a millimeter wave device (e.g., to form a beam in a direction corresponding to certain pixels of the image), and shorten the generation time of millimeter wave image data by identifying based on the selected beamforming pixels.

[0142] While the present disclosure has been shown and described with reference to various embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made without departing from the spirit and scope of the present disclosure as defined by the appended claims and their equivalents.

Claims

1. An electronic device, the electronic device include: a housing, the housing comprising a first plate facing a first direction, a second plate facing away from the first plate, and a side member surrounding a space between the first plate and the second plate; Antenna arrays; an image sensor, the image sensor being arranged to face the first direction; a wireless communication circuit electrically coupled to the antenna array and configured to form a directional beam using the antenna array; a memory storing instructions, reduction patterns of the amplitude of the reflected wave, and a neural network for detecting activity, wherein each of the reduction patterns is associated with each frequency of the reflected wave, and wherein the neural network for detecting activity is trained based on the reduction patterns of the amplitude of the reflected wave; and a processor electrically coupled to the image sensor and the wireless communication circuit; Wherein, when the instructions are executed by the processor, the electronic device: acquiring at least one image using the image sensor, identifying an object in the at least one image, calculating coordinates for transmitting a first directional beam based on the objects identified in the at least one image, transmitting the first directional beam in at least one direction via the antenna array using the calculated coordinates, receiving, via the antenna array, a first reflected wave corresponding to the first directional beam and reflected by the object, identifying the presence of the object based on the at least one image and a first reduction pattern in the amplitude of the first reflected wave, transmitting a second directional beam via the antenna array in at least one direction using coordinates calculated based on the activity detection position of the object for detecting activity, receiving, via the antenna array, a second reflected wave corresponding to the second directional beam and reflected by the object, confirming a score indicating the degree to which the reflected wave matches the second reflected wave, wherein the score is output by the neural network for detecting activity based on a comparison between the decrease pattern and a second decrease pattern of the amplitude of the second reflected wave, and In a case where the confirmed score indicates that the second reduction mode corresponds to the specific reduction mode for the face of a human body among the reduction modes: confirming the presence of activity of said object corresponding to the face, transmitting a third directional beam in at least one direction using coordinates calculated based on the identified position of the object, receiving, via the antenna array, a third reflected wave corresponding to the third directional beam and reflected by the object, and performing authentication of the object corresponding to the face based on the third reflected wave, Wherein, if the activity of the object corresponding to the face is not confirmed, the authentication of the object corresponding to the face is terminated.

2. The electronic device according to claim 1, in, The wireless communication circuit is configured to transmit or receive a signal having a frequency of 3 GHz to 100 GHz, and Wherein, identifying the activity of the object includes: detecting micro-movement of a specific part of the face.

3. The electronic device according to claim 1, in, The instructions, when executed by the processor, cause the electronic device to transmit the first directional beam after identifying the object in the at least one image.

4. The electronic device according to claim 1, in, The at least one direction for the first directional beam is the same as the first direction.

5. The electronic device according to claim 1, in, The instructions, when executed by the processor, cause the electronic device to: determine the at least one direction for the first directional beam based on the identified object.

6. The electronic device according to claim 1, in, The memory stores a reference image and a reference contour of the object, and Wherein, when the instructions are executed by the processor, the electronic device: performs the authentication of the object by comparing the identified object and the outline confirmed by the third reflected wave with the reference image and the reference outline.

7. The electronic device according to claim 1, in, When executed by the processor, the instructions cause the electronic device to determine a distance between the object and the electronic device based on the second reflected wave.

8. The electronic device according to claim 1, in, When the instructions are executed by the processor, the electronic device: performing the authentication of the object while the electronic device is locked, and When the authentication is successful, the state of the electronic device is switched from a locked state to an unlocked state.

9. A method performed by an electronic device, the method include: acquiring at least one image using an image sensor; identifying an object in the at least one image; calculating coordinates for transmitting a first directional beam based on the identified object in the at least one image; transmitting the first directional beam in at least one direction using the calculated coordinates via an antenna array; receiving, via the antenna array, a first reflected wave corresponding to the first directional beam and reflected by the object; identifying the presence of the object based on the at least one image and a first reduction pattern in the amplitude of the first reflected wave; transmitting, via the antenna array, a second directional beam in at least one direction using coordinates calculated based on the activity detection position of the object for detecting activity; receiving, via the antenna array, a second reflected wave corresponding to the second directional beam and reflected by the object; confirming a score indicating the degree to which the reflected wave matches the second reflected wave, wherein the memory of the electronic device stores a reduction pattern of the amplitude of the reflected wave and a neural network for detecting activity, and wherein the score is output by the neural network for detecting activity based on a comparison between the reduction pattern and a second reduction pattern of the amplitude of the second reflected wave; and In a case where the confirmed score indicates that the second reduction mode corresponds to a specific reduction mode for a face of a human body among the reduction modes: confirming the presence of activity of said object corresponding to said face, transmitting a third directional beam in at least one direction using coordinates calculated based on the identified position of the object, receiving, via the antenna array, a third reflected wave corresponding to the third directional beam and reflected by the object, and performing authentication of the object corresponding to the face based on the third reflected wave, wherein, in the case where the activity of the object corresponding to the face is not confirmed, the authentication of the object corresponding to the face is terminated, and wherein each of the reduction patterns is associated with a respective frequency of the reflected wave, and wherein the neural network for detecting activity is trained based on the reduction pattern of the amplitude of the reflected wave.

10. The method according to claim 9, in, The first directional beam is transmitted at a frequency of 3 GHz to 100 GHz, and Wherein, identifying the activity of the object includes: detecting micro-movement of a specific part of the face.

11. The method according to claim 9, further comprising: include: The at least one direction for the first directional beam is determined based on the identified object.

12. The method according to claim 9, in, The memory stores a reference image and a reference contour of the object, and Wherein, the method further comprises: The authentication of the object is performed by comparing the recognized object and the contour confirmed by the third reflected wave with the reference image and the reference contour.

13. The method according to claim 9, further comprising: include: performing the authentication of the object while the electronic device is locked; and When the authentication is successful, the state of the electronic device is switched from a locked state to an unlocked state.

Images