Abstract: A head mounted display (HMD) identifies viewing trends for a video based on multiple viewings of the video by users having different user characteristics. The analysis identifies viewing trends based on user characteristics, e.g., the age and gender of the user. When a subsequent user is viewing the video, a production & post production module receives the user's profile information and identifies the predicted viewing location of the user at particular times during the video using the identified trends based on where previous users/viewers, who have a profile or characteristics similar to the user, were looking at the particular times during the video.

Abstract: A production system determines which areas or portions of a video file (e.g., for a scene) are static and which areas contain motion. Instead of steaming redundant image data for the static areas of the video, the production only sends image data for or updates the areas of each frame that contain motion to minimize an amount of data being streamed to a head mounted display (HMD) without compromising image quality.

Abstract: Variable image data reduction is applied to at least a subset of each frame of a video file. The variable image data reduction includes reducing data by one or more techniques, such as compression, decimation, distortion, and so forth, across the frame by a different degree or amount based on a viewing location of the user. Thus, the amount of data sent to an encoder for delivery to a client device (e.g., head mounted display (HMD) or other computing device) is lowered by prioritizing image quality for the viewing location of the user while one or more data reducing techniques are applied to the remainder of the frame.

Abstract: A production system determines which areas or portions of a video file (e.g., for a scene) are static and which areas contain motion. Instead of steaming redundant image data for the static areas of the video, the production only sends image data for or updates the areas of each frame that contain motion to minimize an amount of data being streamed to a head mounted display (HMD) without compromising image quality.

Abstract: Variable image data reduction is applied to at least a subset of each frame of a video file. The variable image data reduction includes reducing data by one or more techniques, such as compression, decimation, distortion, and so forth, across the frame by a different degree or amount based on a viewing location of the user. Thus, the amount of data sent to an encoder for delivery to a client device (e.g., head mounted display (HMD) or other computing device) is lowered by prioritizing image quality for the viewing location of the user while one or more data reducing techniques are applied to the remainder of the frame.

Abstract: A head mounted display (HMD) identifies viewing trends for a video based on multiple viewings of the video by users having different user characteristics. The analysis identifies viewing trends based on user characteristics, e.g., the age and gender of the user. When a subsequent user is viewing the video, a production & post production module receives the user's profile information and identifies the predicted viewing location of the user at particular times during the video using the identified trends based on where previous users/viewers, who have a profile or characteristics similar to the user, were looking at the particular times during the video.

Abstract: Objects are tracked within images. According to an example embodiment, video data is processed for tracking one or more objects. A computer circuit executes instructions to process a series of ordered video frames in a set of video data as follows. A region of interest is defined in an initial one of the video frames, and a particle mesh is formed from a set of feature points for an object in the defined region. The particle mesh is propagated to an adjacent video frame using motion vectors of points in the mesh to form a coarse boundary at the adjacent frame. Occlusion and scene boundaries are detected in the adjacent video frame, and the detected boundaries are used to set a boundary and a number of feature points within the boundary in the adjacent video frame to maintain mesh coherence and track the object in the subsequent video frames.