Selecting augmented reality objects for display based on contextual cues

Abstract

Various embodiments are disclosed for selecting augmented reality (AR) objects based on contextual cues associated with an image captured by a camera associated with an electronic device. Contextual cues are obtained at an electronic device, and AR objects are identified from a memory associated with the electronic device. The electronic device implements a processor that employs image segmentation techniques to combine the identified AR objects with the captured image, and renders the combined image for display at a display associated with the electronic device.

Description

Background Art

[0001] As processors and other computing modules have become more capable, augmented reality applications and virtual reality applications have become increasingly complex. Virtual reality applications present a virtual environment to a user via a display device such as a head-mounted display, and in some cases allow the user to interact with the virtual environment. In contrast, augmented reality applications merge virtual objects (referred to herein as "augmented reality objects") with images of the user's real environment. Augmented reality applications therefore bring the challenge of merging augmented reality objects with images of the real environment in a way that provides a satisfactory user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0002] The present disclosure may be better understood, and its numerous features and advantages become apparent to those skilled in the art by referencing the accompanying drawings.The use of the same reference numbers in different drawings indicates similar or identical items.

[0003] Figure 1 is a block diagram of an electronic device that selects augmented reality objects in an image of a real environment based on contextual cues in accordance with some embodiments.

[0004] Figure 2 is an example of a networking environment according to various embodiments.

[0005] Figure 3 An exemplary ranking context is illustrated in accordance with some embodiments.

[0006] Figure 4 is a flow diagram illustrating one example of functionality implemented to select an augmented reality object based on contextual cues associated with an image captured by a camera associated with an electronic device in accordance with various embodiments. DETAILED DESCRIPTION

[0007] Figure 1-4 The illustration shows a technique for selecting augmented reality objects for display in an image of a real environment based on contextual cues in accordance with some embodiments. The electronic device includes a camera that captures an image of the real environment and a sensor, such as an inertial measurement unit (IMU) that captures the posture (position and orientation) of the electronic device. Based on contextual cues, such as recognized user expressions, objects or graphics recognized from the captured image, received weather or other environmental information, time of day, sound information, etc., the electronic device selects and modifies augmented reality (AR) objects from memory. The electronic device synthesizes the selected AR object with the captured image to generate a combined image for display. In addition, as the contextual cues change, the electronic device can change the selected AR object to reflect the changed context, thereby improving the user experience.

[0008] Figure 1A block diagram of an electronic device 100 that places an augmented reality object in an image of a real environment based on the posture of the electronic device 100 and based on image segmentation in accordance with some embodiments is illustrated. In some embodiments, the electronic device 100 may include, for example, a server computer or other system that provides computing power. Alternatively, multiple electronic devices 100 that are, for example, arranged in one or more server groups or computer groups or arrangements may be used. For example, multiple electronic devices 100 together may include cloud computing resources, grid computing resources, and / or any other distributed computer components. Such electronic devices 100 may be located in a single device or may be distributed among many different geographical locations. For convenience, the electronic device 100 is referred to in the singular herein. Even if the electronic device 100 is referred to in the singular, it should be understood that multiple electronic devices 100 may be used in various arrangements as described above.

[0009] The electronic device 100 may be any device capable of generating or displaying AR content, including a desktop or laptop computer, a smart phone, a tablet, a game console, etc. Figure 1 For purposes of the exemplary embodiments, it is assumed that electronic device 100 is a smartphone.

[0010] To support the display of AR content, the electronic device 100 includes a camera 102, a processor 104, a memory 105, and a display 110. In at least one embodiment, the camera 102 is a digital camera including one or more image sensors that collectively capture images of the environment of the electronic device 100 (e.g., image 108). In some embodiments, the camera 102 is configured to automatically capture images of the environment without the user having to actuate or intervene in each individual image. For example, as the user moves around the environment, the camera 102 periodically captures images of the environment at specified intervals. As further described herein, the images can be used by the electronic device 100 for one or more applications, such as determining the location of the electronic device 100, identifying objects in the environment of the electronic device 100, and the like.

[0011] The processor 104 is a general or special purpose processor that is typically configured to execute instruction sets (e.g., applications) to perform specified tasks for the electronic device 100 as further described herein. In various embodiments, the processor 104 is a processing device, such as a central processing unit (CPU), a graphics processing unit (GPU), a neural network processor, or a combination thereof, configured to perform operations for the electronic device 100 as further described herein. It should be appreciated that although the processor 104 is illustrated as a single processor for clarity, in some embodiments, the processor 104 can represent a plurality of processing units, each of which includes one or more processor cores or computing units.

[0012] The display 110 is a display device (e.g., a display screen) that is generally configured to display images to a user of the electronic device 100. The display 110 may include, for example, one or more devices such as a cathode ray tube (CRT), a liquid crystal display (LCD) screen, a gas plasma-based flat panel display, an LCD projector, or other types of display devices. In some embodiments, the electronic device 100 includes a network interface (not shown) for connecting the electronic device 100 to a network (e.g., the Internet), from which the electronic device 100 can receive weather information, time information, etc. In addition, in some embodiments, the electronic device 100 includes additional sensors (not shown) for capturing information from the environment of the electronic device 100, such as one or more microphones for capturing sounds in the environment of the electronic device 100.

[0013] The posture sensor 106 includes one or more sensors configured to collectively generate posture information, which is referred to as a posture (e.g., posture 107) reflecting the position, orientation, or combination thereof of the electronic device 100. In at least one embodiment, the posture sensor 106 includes an inertial measurement unit (IMU). The posture sensor 106 can include other or additional posture sensors, such as a global positioning satellite (GPS) sensor. In at least one embodiment, the posture sensor 106 can also include a simultaneous positioning and mapping (SLAM) module that generates a map of the environment of the electronic device 100 based on objects identified in the image captured by the camera 102. The SLAM module identifies objects according to conventional machine vision techniques and compares the objects with an object cache (not shown) stored at the electronic device 100 or at a remote server communicating with the electronic device 100 via a network (e.g., via the Internet). The position of the object in the object cache is known, so that the SLAM module can generate an environmental map based on object comparison. Therefore, the posture generated by the posture sensor 106 can be based on a combination of sensors, such as a combination of IMU data and SLAM mapping information.

[0014] The memory 105 is a computer memory, such as a random access memory (RAM), a flash memory, or a combination thereof, configured to store data for access by the processor 104. As can be appreciated, the memory 105 may represent a plurality of memories 105. For example, the data stored in the memory 105 is associated with the operation of the various applications and / or functional entities described below.

[0015] exist Figure 1In an example of AR objects, memory 105 stores AR objects (e.g., AR objects 115 and 116), sometimes referred to as "stickers", for display via display 110. Examples of AR objects can include graphic images (e.g., images of characters from a movie, television show, musicians, etc.), emoticons, cartoon characters, weather images, generated text, etc. In some embodiments, the AR objects can be modified by processor 104. For example, one or more of the AR objects can include a modifiable text string that can be changed by processor 104, one or more color features where the color can be changed by processor 104, an orientation can be associated with one or more of the AR objects where the orientation can be changed by processor 104, lighting can be associated with one or more of the AR objects where the lighting can be changed, etc.

[0016] In operation, the processor 104 combines the image captured by the camera 108 with one or more AR objects to generate a combined image (e.g., combined image 118) and displays the combined image at the display 110. In some embodiments, the processor 104 generates the combined image by segmenting the captured image into foreground pixels and background pixels. To segment the image, the processor 104 can apply any image segmentation method or combination thereof, including pixel thresholding, data clustering, motion and interactive segmentation, compression-based segmentation, histogram-based segmentation, edge detection, dual clustering, region growing, partial differential equation segmentation (e.g., parameter, level set or fast marching), variational segmentation, watershed transform, model-based segmentation, multi-scale segmentation, semi-automatic segmentation, trainable segmentation, multi-spectral segmentation, etc. For example, in at least one embodiment, the processor 104 employs segmentation or other object recognition techniques to identify one or more graphics in the foreground of a captured image (e.g., image 108), such as a graphic of a user in a self-photo ("selfie"). The processor 104 identifies pixels representing the identified graphics as foreground pixels and identifies all other pixels of the captured image as background pixels. The processor 104 generates a combined image 118 by combining the selected and modified AR object with the captured image 108 .

[0017] In some embodiments, the processor 104 selects and modifies an AR object for display based on one or more contextual cues or a combination thereof, wherein the contextual cues can be generated based on images captured by the camera 102, by gesture information generated by the gesture sensor 106, by information received via a network (e.g., weather information received via the Internet), sensor information received from sensors of the electronic device 100 (e.g., sound information received via one or more microphones), etc., or by any combination thereof. To illustrate by way of example, if the processor 104 receives weather information indicating rainy weather in the location of the electronic device 100, the processor 104 can select an AR object representing clouds or rain. If the processor 104 receives information indicating a loud noise in the environment of the electronic device 100, the processor 104 can select an object indicating a bang! sound.

[0018] In some embodiments, processor 104 can select an AR object based on detected emotions of one or more persons identified in imagery captured by camera 102. To identify emotions, processor 104 can execute one or more facial and emotion recognition algorithms that identify points on a user's face and identify emotions based on specified relationships between the identified points. For example, the relationship between the points can indicate that a person is smiling, frowning, or expressing other emotions. Examples of AR objects that can be selected or modified based on identified emotions include:

[0019]

[0020] refer to Figure 2 , shows a networked environment 200 according to various embodiments. The networked environment 200 includes an electronic device 100 having one or more client devices (not shown) and a network 209. The network 209 includes, for example, the Internet, an intranet, an extranet, a wide area network (WAN), a local area network (LAN), a wired network (LAN), a wired network, a wireless network, or other suitable network, or any combination of two or more such networks.

[0021] According to various embodiments, various applications and / or other functionalities may be executed in the electronic device 100. In addition, various data are stored in a memory 105 accessible to the electronic device 100. In some embodiments, the electronic device 100 is configured to capture an image 108 and employ a processor 104 to obtain one or more context clues from the image 108. For example, context clues obtained from the image 108 may include a person, a facial expression, a sound, a location, a time, a date, an activity, weather information, an item, or a combination thereof. To this end, the image 108 may include a person, a group of people, a self-portrait image, and the mood of the person depicted in the image. For example, the image 108 may depict a smiling person. In this example, the electronic device 100 may be configured to implement the processor 104 to obtain context clues indicating a happy mood associated with the person. In some embodiments, the AR object is configured to dynamically react in response to changes in facial expressions associated with the user depicted in the camera view. For example, in response to detecting a person depicted in the camera view, the AR object may be configured to confirm the person so that the AR object is configured to nod, wave, smile, and / or perform other gestures. Additionally, the AR object may be configured to respond to changes in facial expressions or movements associated with a human face, such as blinking, raising eyebrows, up and down eye movements, left and right eye movements, moth frowning, mouth smiling, and / or other movements associated with the user's face. For example, in response to detecting a user's smile, the AR object may be configured to smile. In other embodiments, contextual cues may be associated with objects or items such as, for example, food, artwork, water, plants, clothing articles, animals, and / or any other curated objects. In other embodiments, contextual cues may be associated with activities such as vacations, shopping, running, swimming, hiking, attending sporting events, attending concerts, and / or other activities. In still other embodiments, contextual cues may be associated with locations such as, for example, countries, states, homes, offices, schools, restaurants, specific landmarks, and / or other locations. In another embodiment, contextual cues may be associated with, for example, time of day, day of the week, month of the year, vacation, and / or time. In some embodiments, contextual cues may be associated with sounds such as, for example, musical instruments, people, songs, music, and / or other sounds. In other embodiments, the contextual cues may be associated with weather information such as, for example, snow, rain, monsoon, thunder, lightning, tornado, hurricane, sunset, sunrise, and / or other weather information. In still other embodiments, the contextual cues may be based on one or more images captured by a camera associated with the electronic device 100, information generated by one or more sensors associated with the electronic device, information received via a network 209 associated with the electronic device 100, or a combination thereof.

[0022] In some embodiments, in response to receiving contextual cues associated with the image 108, the processor 104 identifies at least one augmented reality (AR) object 115, 116 from the memory 105, such that the AR objects 115, 116 are identified based on the contextual cues received by the electronic device 100. In some embodiments, the AR objects 115, 116 are identified based on a selection made by a user.

[0023] As explained above, upon identifying the AR objects 115, 116, the processor 104 is also configured to combine the image 108 with the identified AR objects 115, 116 and display the combined image 118 at the display 110. In some embodiments, the processor 104 may employ image segmentation techniques to generate the combined image 118.

[0024] Additionally, in some embodiments, the processor 104 may be utilized by the electronic device 100 to change and / or modify the identified AR objects 115, 116 based on changes in one or more contextual cues. In other embodiments, once the AR objects 115, 116 are identified by the processor 104, the processor 104 is further configured to rank the identified AR objects 115, 116 based on confidence metrics associated with the identified AR objects 115, 116 and present a collection of AR objects 115, 116 based on the rankings. In other embodiments, the electronic device 100 may be configured to receive one or more contextual cues obtained from a sensor such as, for example, a gesture sensor 106 associated with the electronic device.

[0025] Figure 3 An exemplary ranking context 300 is shown in accordance with some embodiments. For example, in some embodiments, the context clues 303(a)-303(n) are ranked based on a confidence metric associated with the context clues 303(a)-303(n). In some embodiments, the confidence metric indicates a degree of relevance between the context clue and the identified AR object. To this end, the processor 104( Figure 1) are ranked as general to specific spectrum based on their corresponding confidence metrics. In some embodiments, context clues 303(a) with lower confidence metrics can be identified as general context clues. Context clues 303(n) with higher confidence metrics can be identified as specific context clues. For example, in some embodiments, context clues 303(a)-303(n) can include people, objects, activities, locations, dates, times, sounds, weather and / or context clues. For each of the context clues 303(a)-303(n), processor 104 can be configured to calculate a confidence metric. In some embodiments, the confidence metric can be calculated by adding together the relevant signals associated with each context clue and assigning a score by context. As an example, the confidence metric can be based on the number of context clues associated with a specific context. Similarly, in these embodiments, the processor 104 is configured to identify the AR objects 115, 116 based on the confidence metrics associated with the AR objects 115, 116 ( Figure 1 ) are ranked. Likewise, in these embodiments, the identified general AR objects may be ranked lower than the identified specific AR objects. In these embodiments, the processor 104 may be configured to present the identified AR objects 115, 116 for rendering on the display 110 based on the ranking.

[0026] Next reference Figure 4 , shows a flowchart of an example of a method for selecting an augmented reality object for display in an image of a real environment based on contextual cues in accordance with some embodiments. It should be understood that Figure 4 The flowchart of is merely an example of many different types of arrangements that may be employed to select augmented reality objects for display based on contextual cues as described herein. As an alternative, Figure 4 The flowchart of is considered as an example of describing the steps of the method implemented in the electronic device according to various embodiments. It should be understood that the process can be different depending on the specific situation. In addition, it should be understood that other processes are adopted in addition to the processes discussed in this article.

[0027] Beginning in block 403, the electronic device 100 ( Figure 1 ) via a processor 104 ( configured to identify contextual cues 303 ( a )- 303 ( n ) from an image 108 Figure 1 ) to obtain contextual cues 303(a)-303(n) associated with image 108 ( Figure 3). For example, in some embodiments, the electronic device 100 includes a camera that captures images of the real environment. In box 406, the electronic device 100 uses the processor 104 to detect the context based on context cues, such as recognized user expressions, objects or graphics recognized from the captured images, received weather or other environmental information, time of day, sound information, etc. Next, in box 409, in response to receiving the context cues associated with the image 108, the electronic device 100 is configured to implement the processor 104 to identify and / or select at least one augmented reality (AR) object 115, 116 from the memory 105, so that the AR objects 115, 116 are identified based on the context cues received by the electronic device 100. In box 412, the processor 104 is configured to identify the identified AR objects 115, 116 based on the confidence metrics associated with the AR objects 115, 116 ( Figure 1 ) are ranked. Likewise, in these embodiments, the identified general AR object may be ranked lower than the identified specific AR object. In these embodiments, the processor 104 may be configured to present the identified AR objects 115, 116 for rendering on the display 110 based on the ranking. In box 415, the electronic device 100 utilizes the processor 104 to synthesize the identified and / or selected AR objects 115, 116 with the captured image to generate a combined image for display. In box 415, the electronic device 100 implements the processor 104 to render the combined image 118 for display at the display 100 associated with the electronic device 100.

[0028] In some embodiments, certain aspects of the above-mentioned techniques may be implemented by one or more processors of a processing system executing software. The software includes one or more executable instruction sets stored or otherwise tangibly embodied on a non-transitory computer-readable storage medium. The software can include instructions and certain data that, when executed by one or more processors, manipulate one or more processors to perform one or more aspects of the above-mentioned techniques. The non-transitory computer-readable storage medium can include, for example, a magnetic or optical disk storage device, a solid-state storage device such as a flash memory, a cache, a random access memory (RAM), or one or more other non-volatile memory devices, etc. The executable instructions stored on the non-transitory computer-readable storage medium may be in source code, assembly language code, object code, or other instruction formats that are interpreted or otherwise executable by one or more processors.

[0029] Computer-readable storage media may include any storage media or combination of storage media that can be accessed by a computer system during use to provide instructions and / or data to the computer system. Such storage media can include, but are not limited to, optical media (e.g., compact disk (CD), digital versatile disk (DVD), Blu-ray disk), magnetic media (e.g., floppy disk, tape, or magnetic hard drive), volatile memory (e.g., random access memory (RAM) or cache), non-volatile memory (e.g., read-only memory (ROM) or flash memory), or storage media based on microelectromechanical systems (MEMS). Computer-readable storage media can be embedded in a computing system (e.g., system RAM or ROM), fixedly attached to a computing system (e.g., a magnetic hard drive), removably attached to a computing system (e.g., an optical disk or flash memory based on a universal serial bus (USB)), or coupled to a computer system via a wired or wireless network (e.g., network accessible storage (NAS)).

[0030] Note that not all activities or elements described above in the general description are required, a portion of a particular activity or device may not be required, and one or more additional activities may be performed, or elements other than the described elements may be included. Furthermore, the order in which the activities are listed is not necessarily the order in which the activities are performed. In addition, the concept has been described with reference to specific embodiments. However, it will be appreciated by those of ordinary skill in the art that various modifications and changes can be made without departing from the scope of the present disclosure as set forth in the following claims. Therefore, the specification and the drawings will be considered in an illustrative rather than a restrictive sense, and all such modifications are intended to be included within the scope of the present disclosure.

[0031] Benefits, other advantages, and solutions to problems have been described above with respect to specific embodiments. However, benefits, advantages, solutions to problems, and any features that can make any benefit, advantage, or solution occur or become more significant should not be interpreted as key, essential, or necessary features of any or all claims. In addition, the specific embodiments disclosed above are merely illustrative, as the disclosed subject matter can be modified and practiced in different but equivalent ways that are obvious to those skilled in the art who benefit from the teachings herein. Except as described in the following claims, it is not intended to be limited to the details of construction or design shown herein. It is therefore apparent that the specific embodiments disclosed above can be changed or modified, and all such changes are considered to be within the scope of the disclosed subject matter. Therefore, the protection sought herein is as set forth in the following claims.

[0032] Some examples are described below.

[0033] Example 1: A method comprising:

[0034] Obtaining one or more contextual cues at an electronic device;

[0035] identifying at least one augmented reality (AR) object from a memory associated with the electronic device based on the one or more contextual cues;

[0036] combining the image with the identified at least one AR object; and

[0037] The combined image is displayed at a display associated with the electronic device.

[0038] Example 2: The method according to Example 1, wherein the context clues include people, facial expressions, sounds, locations, time, date, activities, weather information, items, or a combination thereof.

[0039] Example 3: The method according to Example 1 or 2 also includes using image segmentation to generate the combined image.

[0040] Example 4: The method of at least one of the preceding examples further comprising changing at least one identified AR object based on a change in the one or more contextual cues.

[0041] Example 5: The method according to at least one of the preceding examples, further comprising:

[0042] ranking the at least one identified AR object based on a confidence metric associated with the at least one identified AR object; and

[0043] A collection of AR objects is presented based on the ranking.

[0044] Example 6: The method according to at least one of the preceding examples further includes identifying the one or more contextual cues from the image.

[0045] Example 7: The method of at least one of the preceding examples further comprises receiving the one or more contextual cues from a sensor associated with the electronic device.

[0046] Example 8: The method of at least one of the preceding examples, wherein the identified at least one AR object is based on a user selection.

[0047] Example 9: A system comprising:

[0048] a memory configured to store at least one augmented reality (AR) object;

[0049] a processor configured to combine the image from the memory with a recognized one of the at least one AR object, wherein the recognized one of the at least one AR object is recognized based on one or more contextual cues associated with the image; and

[0050] A display is configured to display the combined image.

[0051] Example 10: The system of Example 9, wherein the processor is configured to change the at least one identified object in response to a change in the one or more contextual cues.

[0052] Example 11: The system of Example 9 or 10, wherein the processor is further configured to:

[0053] ranking the at least one identified AR object based on a confidence metric associated with the at least one identified AR object; and

[0054] A set of identified AR objects is presented based on the ranking.

[0055] Example 12: A system according to at least one of Examples 9 to 11, wherein the contextual cues include people, facial expressions, sounds, locations, times, dates, activities, weather information, items, or combinations thereof.

[0056] Example 13: According to the system of at least one of Examples 9 to 12, the processor is further configured to obtain the one or more contextual cues from a sensor.

[0057] Example 14: According to the system of at least one of Examples 9 to 13, the processor is further configured to use image segmentation to combine the image with the identified at least one AR object.

[0058] Example 15: According to the system of at least one of Examples 9 to 14, the at least one AR object identified is based on a user selection.

[0059] Example 16: A non-transitory computer readable medium containing an executable set of instructions for manipulating a computer system to perform a portion of a process for making at least a portion of a processor, the processor comprising:

[0060] a combining component configured to combine an image from a memory associated with an electronic device with at least one recognized augmented reality (AR) object, the recognized at least one AR object being recognized based on one or more contextual cues received by the electronic device; and

[0061] A display is configured to display the combined image.

[0062] Example 17: According to the non-transitory computer-readable medium of Example 16, the one or more context clues are based on one or more images captured by a camera associated with the electronic device, information generated by one or more sensors associated with the electronic device, information received via a network associated with the electronic device, or a combination thereof.

[0063] Example 18: According to the non-transitory computer-readable medium of Example 16 or 17, the processor is also configured to use image segmentation to generate the combined image.

[0064] Example 19: According to the non-transitory computer-readable medium of at least one of Examples 16 to 18, the processor is further configured to modify the identified at least one AR object.

[0065] Example 20: According to the non-transitory computer-readable medium of at least one of Examples 16 to 19, at least one identified AR object is modified based on a change in the one or more contextual cues.

Claims

1. A method comprising: Obtaining one or more contextual cues at an electronic device; identifying a plurality of augmented reality (AR) objects from a memory associated with the electronic device based on the one or more contextual cues; ranking the plurality of AR objects based on a confidence metric associated with each of the one or more contextual cues, and selecting at least one AR object from the plurality of AR objects based at least in part on the ranking; combining the image with the selected at least one AR object; as well as The combined image is displayed at a display associated with the electronic device.

2. The method according to claim 1, wherein: The contextual cues include people, facial expressions, sounds, locations, time, date, activities, weather information, items, or a combination thereof. The method of claim 1 , further comprising using image segmentation to generate the combined image. 4 . The method of claim 1 , further comprising changing the selected at least one AR object based on a change in the one or more contextual cues.

5. The method according to claim 1, further comprising: A collection of AR objects is presented based on the ranking. The method of claim 1 , further comprising identifying the one or more contextual cues from the image.

7. The method of claim 1, further comprising receiving the one or more contextual cues from a sensor associated with the electronic device.

8. The method according to claim 1, wherein: Selecting the at least one AR object is further based on a user selection.

9. A system comprising: A memory configured to store a plurality of augmented reality (AR) objects; A processor configured to: identifying a plurality of augmented reality (AR) objects from the memory based on one or more contextual cues; ranking the plurality of AR objects based on a confidence metric associated with each of the one or more contextual cues; selecting at least one AR object from the plurality of AR objects based at least in part on the ranking; combining the image from the memory with the selected at least one AR object; as well as A display is configured to display the combined image.

10. The system according to claim 9, wherein: The processor is configured to change the selected at least one AR object in response to a change in the one or more contextual cues.

11. The system according to claim 9, wherein: The processor is further configured to: A set of identified AR objects is presented based on the ranking.

12. The system according to claim 9, wherein: The contextual cues include people, facial expressions, sounds, locations, time, date, activities, weather information, items, or a combination thereof.

13. The system according to claim 9, wherein: The processor is further configured to obtain the one or more contextual cues from a sensor.

14. The system according to claim 9, wherein: The processor is further configured to employ image segmentation to combine the image with the selected at least one AR object.

15. The system according to claim 9, wherein: The selected at least one AR object is further based on a user selection.

16. A non-transitory computer readable medium containing an executable set of instructions for manipulating a computer system to perform a portion of a process for making at least a portion of a processor, the processor comprising: a ranking component configured to identify a plurality of augmented reality (AR) objects from a memory associated with the electronic device based on confidence metrics associated with one or more contextual cues, and to rank the plurality of AR objects based at least in part on the associated confidence metrics; a combining component configured to combine the image with the selected at least one augmented reality (AR) object, the selected at least one AR object being selected based at least in part on a ranking assigned to the at least one AR object; as well as A display is configured to display the combined image.

17. The non-transitory computer readable medium of claim 16, wherein: The one or more contextual cues are based at least in part on one or more images captured by a camera associated with the electronic device, information generated by one or more sensors associated with the electronic device, information received via a network associated with the electronic device, or a combination thereof.

18. The non-transitory computer readable medium of claim 16, wherein: The processor is also configured to employ image segmentation to generate the combined image.

19. The non-transitory computer readable medium of claim 16, wherein: The processor is further configured to modify the selected at least one AR object.

20. The non-transitory computer readable medium of claim 16, wherein: The selected at least one AR object is modified based on the change in the one or more contextual cues.

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