Abstract:
Techniques are disclosed for performing avatar-based video encoding. In some embodiments, a video recording of an individual may be encoded utilizing an avatar that is driven by the facial expression(s) of the individual. In some such cases, the resultant avatar animation may accurately mimic facial expression(s) of the recorded individual. Some embodiments can be used, for example, in video sharing via social media and networking websites. Some embodiments can be used, for example, in video-based communications (e.g., peer-to-peer video calls; videoconferencing). In some instances, use to the disclosed techniques may help to reduce communications bandwidth use, preserve the individual's anonymity, and/or provide enhanced entertainment value (e.g., amusement) for the individual, for example.
Abstract:
Systems and methods may provide for detecting a condition with respect to one or more frames of a video signal associated with a set of facial motion data and modifying, in response to the condition, the set of facial motion data to indicate that the one or more frames lack facial motion data. Additionally, an avatar animation may be initiated based on the modified set of facial motion data. In one example, the condition is one or more of a buffer overflow condition and a tracking failure condition.
Abstract:
Apparatuses, methods and storage medium associated with animating and rendering an avatar are disclosed herein. In embodiments, the apparatus may include a gesture tracker and an animation engine. The gesture tracker may be configured to detect and track a user gesture that corresponds to a canned facial expression, the user gesture including a duration component corresponding to a duration the canned facial expression is to be animated. Further, the gesture tracker may be configured to respond to a detection and tracking of the user gesture, and output one or more animation messages that describe the detected/tracked user gesture or identify the canned facial expression, and the duration. The animation engine may be configured to receive the one or more animation messages, and drive an avatar model, in accordance with the one or more animation messages, to animate the avatar with animation of the canned facial expressions for the duration. Other embodiments may be described and/or claimed.
Abstract:
Systems and methods may provide for identifying one or more facial expressions of a subject in a video signal and generating avatar animation data based on the one or more facial expressions. Additionally, the avatar animation data may be incorporated into an audio file associated with the video signal. In one example, the audio file is sent to a remote client device via a messaging application. Systems and methods may also facilitate the generation of avatar icons and doll animations that mimic the actual facial features and/or expressions of specific individuals.
Abstract:
Techniques related to game focus estimation in team sports for multi-camera immersive video are discussed. Such techniques include selecting regions of a scene comprising a sporting event, generating a node graph and sets of features for the selected regions, and determining a game focus region of the selected regions by applying a graph node classification model based on the node graph and sets of features.
Abstract:
A mechanism is described for facilitating real-time multi-view detection of objects in multi-camera environments, according to one embodiment. A method of embodiments, as described herein, includes mapping first lines associated with objects to a ground plane; and forming clusters of second lines corresponding to the first lines such that an intersection point in a cluster represents a position of an object on the ground plane.
Abstract:
A multi-camera architecture for detecting and tracking a ball in real-time. The multi-camera architecture includes network interface circuitry to receive a plurality of real-time videos taken from a plurality of high-resolution cameras. Each of the high-resolution cameras simultaneously captures a sports event, wherein each of the plurality of high-resolution cameras includes a viewpoint that covers an entire playing field where the sports event is played. The multi-camera architecture further includes one or more processors coupled to the network interface circuitry and one or more memory devices coupled to the one or more processors. The one or more memory devices includes instructions to determine the location of the ball for each frame of the plurality of real-time videos, which when executed by the one or more processors, cause the multi-camera architecture to simultaneously perform one of a detection scheme or a tracking scheme on a frame from each of the plurality of real-time videos to detect the ball used in the sports event and perform a multi-camera build to determine a location of the ball in 3D for the frame from each of the plurality of real-time videos using one of detection or tracking results for each of the cameras.
Abstract:
Methods, systems and apparatuses may provide for technology that automatically determines, based on camera calibration data and trajectory data associated with a projectile in a game, a plurality of camera angles. The technology may also automatically generate, based on the plurality of camera angles, a camera path for a volumetric content replay of a three-dimensional (3D) region of interest around a highlight moment in the game.
Abstract:
A method for trajectory generation based on player tracking is described herein. The method includes determining a temporal association for a first player in a captured field of view and determining a spatial association for the first player. The method also includes deriving a global player identification based on the temporal association and the spatial association and generating a trajectory based on the global player identification.
Abstract:
Methods and apparatus to generate photo-realistic three-dimensional models of a photographed environment are disclosed. An apparatus includes an object position calculator to determine a three-dimensional (3D) position of an object detected within a first image of an environment and within a second image of the environment. The apparatus further includes a 3D model generator to generate a 3D model of the environment based on the first image and the second image. The apparatus also includes a model integrity analyzer to detect a difference between the 3D position of the object and the 3D model. The 3D model generator automatically modifies the 3D model based on the difference in response to the difference satisfying a confidence threshold.