Abstract: Embodiments disclose systems and methods for transmitting user-extracted video and content more efficiently by recognizing that user-extracted video provides the potential to treat parts of a single frame of a user-extracted video differently. An alpha mask of the image part of the user-extracted video is used when encoding the image part so that it retains a higher quality upon transmission than the remainder of the user-extracted video.

Abstract: Disclosed herein are methods and systems for classifying pixels as foreground using both short-range depth data and long-range depth data. One embodiment takes the form of a process that includes obtaining video data depicting at least a portion of a user. The process also includes obtaining short-range depth data associated with the video data. The process also includes obtaining long-range depth data associated with the video data. The video data, short-range depth data, and long-range depth data may be obtained via a single 3-D video camera. The process also includes classifying pixels of the video data as foreground based at least in part on both the short-range depth data and the long-range depth data. In some embodiments, classifying pixels of the video data as foreground comprises employing an alpha mask. The alpha mask may comprise binary foreground (hard) indicators. The alpha mask may comprise foreground-likelihood (soft) indicators.

Abstract: Disclosed herein are methods and systems for assigning pixels distance-cost values using a flood fill technique. One embodiment takes the form of a process that includes obtaining video data depicting a head of a user, obtaining depth data associated with the video data, and selecting seed pixels for a flood fill at least in part by using the depth information. The process also includes performing the flood fill from the selected seed pixels. The flood fill assigns respective distance-cost values to pixels of the video data based on position-space cost values and color-space cost values. In some embodiments, the process also includes classifying pixels of the video data as foreground based at least in part on the assigned distance-cost values. In some other embodiments, the process also includes assigning pixels of the video data foreground-likelihood values based at least in part on the assigned distance-cost values.

Abstract: Disclosed herein are systems and methods for iterative adjustment of video-capture settings based on identified persona. In an embodiment, a method includes receiving video frames that are being captured by a video camera of an ongoing scene. The method also includes identifying a persona in one or more of the received frames at least in part by identifying, in each such frame, a set of pixels classified as being representative of the persona. The method also includes selecting, based collectively on the brightness values of the pixels in the identified set, a respective adjustment command for one or more adjustable video-capture settings of the camera, as well as outputting the selected commands to the camera for use in continuing to capture video data representative of the ongoing scene.

Abstract: Systems and methods for using geometric primitives to identify background in video data. In one embodiment, a method obtains video data depicting at least a portion of a user. The video data is processed with at least one persona identification module comprising a geometric primitive module for generating a first persona probability map at least in part by: detecting at least one geometric primitive within the video data; identifying a respective region within the video data associated with each of the at least one detected geometric primitives; and assigning the respective regions an increased background-probability in the first persona probability map; and outputting a persona image by extracting pixels from the video data based on the persona probability map.

Abstract: Methods and systems for real-time user extraction using deep learning networks. In one embodiment, user extraction comprises obtaining a given frame of color pixel data, checking whether a reset flag is cleared or set, and generating a trimap for the given frame. If the reset flag is cleared, generating the trimap comprises: obtaining a user-extraction contour based on a preceding frame; and generating the trimap based on the obtained user-extraction contour. If the reset flag is set, generating the trimap comprises: detecting at least one persona feature in the given frame; generating an alpha mask by aligning an intermediate contour with the detected persona feature(s), wherein the intermediate contour is based on a color-based flood-fill operation performed on a previous frame which was segmented by a machine-learning-segmentation process; and generating the trimap based on the generated alpha mask. The generated trimap is output for extracting a user persona.

Abstract: Disclosed herein are methods and systems for combining foreground video and background video using chromatic matching. In an embodiment, a system obtains foreground video data. The system obtains background video data. The system determines a color-distribution dimensionality of the background video data to be either high-dimensional chromatic or low-dimensional chromatic. The system selects a chromatic-adjustment technique from a set of chromatic-adjustment techniques based on the determined color-distribution dimensionality of the background video data. The system adjusts the foreground video data using the selected chromatic-adjustment technique. The system generates combined video data at least in part by combining the background video data with the adjusted foreground video data. The system outputs the combined video for display.

Abstract: Embodiments disclose extracting a user persona from a video of arbitrary duration and associating that persona with text for a chat session. Embodiments cause the persona to be extracted at the moment text is sent or received to convey the body language associated with the text.

Abstract: Disclosed herein are systems and methods for persona identification using combined probability maps. An embodiment takes the form of a method that includes obtaining at least one frame of pixel data; processing the at least one frame of pixel data to generate a hair-identification probability map; and generating a persona image by extracting pixels from the at least one frame of pixel data based at least in part on the generated hair-identification probability map.

Abstract: Described herein are methods and systems for visually deemphasizing a displayed persona. At least one embodiment takes the form of a method carried out by a user-interface (UI)-management device. The UI-management device identifies a persona region of a displayed persona and identifies a user-interface-focus location. The UI-management device then makes a persona-deemphasize determination based on the identified persona region and the identified user-interface-focus location. In response to making the persona-deemphasize determination, the UI-management device visually deemphasizes the displayed persona.

Abstract: A color image and a depth image of a live video are received. Each of the color image and the depth image are processed to identify the foreground and the background of the live video. The background of the live video is removed in order to create a foreground video that comprises the foreground of the live video. A control input may be received to control the embedding of the foreground video into a second background from a background feed. The background feed may also comprise virtual objects such that the foreground video may interact with the virtual objects.

Abstract: Disclosed herein are methods and systems for generating a user-hair-color model. One embodiment takes the form of a process that includes obtaining video data depicting a head of a user. The process also includes determining a set of line segments of pixels of the video data, wherein each line segment in the determined set of line segments intersects an upper contour of the depicted head of the user. The process also includes grouping at least some of the pixels of at least one of the line segments in the determined set of line segments into three sets of pixels based at least in part on respective color data of the pixels. The three sets of pixels include a skin-pixel set, a hair-pixel set, and a background-pixel set. The process also includes updating a user hair-color model based at least in part on the skin-pixel set.

Abstract: Disclosed herein are methods and systems for assigning pixels distance-cost values using a flood fill technique. One embodiment takes the form of a process that includes obtaining video data depicting a head of a user, obtaining depth data associated with the video data, and selecting seed pixels for a flood fill at least in part by using the depth information. The process also includes performing the flood fill from the selected seed pixels. The flood fill assigns respective distance-cost values to pixels of the video data based on position-space cost values and color-space cost values. In some embodiments, the process also includes classifying pixels of the video data as foreground based at least in part on the assigned distance-cost values. In some other embodiments, the process also includes assigning pixels of the video data foreground-likelihood values based at least in part on the assigned distance-cost values.

Abstract: Disclosed herein are systems and methods for iterative adjustment of video-capture settings based on identified persona. In an embodiment, a method includes receiving video frames being captured by a video camera of an ongoing scene. The method also includes identifying a persona in one or more of the received frames at least in part by identifying, in each such frame, a set of pixels that is representative of the persona in the frame and that does not include any pixels representative of a background of the frame. The method also includes selecting, based collectively on the brightness values of the pixels in the identified set of pixels of one or more frames, an adjustment command for one or more adjustable video-capture settings of the camera, as well as outputting the selected commands to the camera for use in continuing to capture video data representative of the ongoing scene.

Abstract: Disclosed herein are systems and methods for extracting person image data comprising: obtaining at least one frame of pixel data and corresponding image depth data; processing the at least one frame of pixel data and the image depth data with a plurality of persona identification modules to generate a corresponding plurality of persona probability maps; combining the plurality of persona probability maps to obtain an aggregate persona probability map; and generating a persona image by extracting pixels from the at least one frame of pixel data based on the aggregate persona probability map.

Abstract: Embodiments disclose systems and methods for transmitting user-extracted video and content more efficiently by recognizing that user-extracted video provides the potential to treat parts of a single frame of a user-extracted video differently. An alpha mask of the image part of the user-extracted video is used when encoding the image part so that it retains a higher quality upon transmission than the remainder of the user-extracted video.

Abstract: A method, apparatus, system, and computer program product for of digital imaging. Multiple cameras comprising lenses and digital images sensors are used to capture multiple images of the same subject, and process the multiple images using difference information (e.g., an image disparity map, an image depth map, etc.). The processing commences by receiving a plurality of image pixels from at least one first image sensor, wherein the first image sensor captures a first image of a first color, receives a stereo image of the first color, and also receives other images of other colors. Having the stereo imagery, then constructing a disparity map and an associated depth map by searching for pixel correspondences between the first image and the stereo image. Using the constructed disparity map, captured images are converted into converted images, which are then combined with the first image, resulting in a fused multi-channel color image.

Abstract: Disclosed herein are methods and systems for presenting personas according to a common cross-client configuration. An embodiment takes the form of a method that includes extracting a persona from video frames being received from a video camera. The method also includes transmitting an outbound stream of persona data that includes the extracted persona. The method also includes receiving at least one inbound stream of persona data, where the at least one inbound stream of persona data includes one or more other personas. The method also includes presenting a full persona set of the extracted persona and the one or more other personas on a user interface according to a common cross-client persona configuration. The method also includes presenting one or more shared-content channels on the user interface according to a common cross-client shared-content-channel configuration.

Abstract: Disclosed herein are systems and methods for iterative adjustment of video-capture settings based on identified persona. In an embodiment, a method includes receiving video frames being captured by a video camera of an ongoing scene. The method also includes identifying a persona in one or more of the received frames at least in part by identifying, in each such frame, a set of pixels that is representative of the persona in the frame and that does not include any pixels representative of a background of the frame. The method also includes selecting, based collectively on the brightness values of the pixels in the identified set of pixels of one or more frames, an adjustment command for one or more adjustable video-capture settings of the camera, as well as outputting the selected commands to the camera for use in continuing to capture video data representative of the ongoing scene.

Abstract: Disclosed herein are systems and methods for extracting person image data comprising: obtaining at least one frame of pixel data and corresponding image depth data; processing the at least one frame of pixel data and the image depth data with a plurality of persona identification modules to generate a corresponding plurality of persona probability maps; combining the plurality of persona probability maps to obtain an aggregate persona probability map; and generating a persona image by extracting pixels from the at least one frame of pixel data based on the aggregate persona probability map.