Abstract:
Systems and processes for improved video editing, summarization and navigation based on generation and analysis of metadata are described. The metadata may be content-based (e.g., differences between neighboring frames, exposure data, key frame identification data, motion data, or face detection data) or non-content-based (e.g., exposure, focus, location, time) and used to prioritize and/or classify portions of video. The metadata may be generated at the time of image capture or during post-processing. Prioritization information, such as a score for various portions of the image data may be based on the metadata and/or image data. Classification information such as the type or quality of a scene may be determined based on the metadata and/or image data. The classification and prioritization information may be metadata and may be used to automatically remove undesirable portions of the video, generate suggestions during editing or automatically generate summary video.
Abstract:
Systems, methods, and a computer readable medium for performing auto exposure (AE) techniques that are beneficial in variable lighting conditions—and particularly applicable to handheld and/or mobile videoconferencing applications—are disclosed herein. Handheld and/or mobile videoconferencing applications—unlike their fixed camera counterparts—are often exposed to a wide variety of rapidly changing lighting and scene conditions, and thus face a difficult trade-off between adjusting exposure parameter values too frequently or not frequently enough. In personal electronic devices executing such handheld and/or mobile videoconferencing applications, it may be desirable to: use a small, centered, and center-weighted exposure metering region; set a relatively low brightness target value; and adjust the camera's exposure parameter values according to a distance-dependent convergence speed function. The use of such techniques, in conjunction with a relatively large stability region, may also improve the quality of a video encoder's temporal predictions—and thus video quality—in videoconferencing applications.
Abstract:
Systems and processes for improved video editing, summarization and navigation based on generation and analysis of metadata are described. The metadata may be content-based (e.g., differences between neighboring frames, exposure data, key frame identification data, motion data, or face detection data) or non-content-based (e.g., exposure, focus, location, time) and used to prioritize and/or classify portions of video. The metadata may be generated at the time of image capture or during post-processing. Prioritization information, such as a score for various portions of the image data may be based on the metadata and/or image data. Classification information such as the type or quality of a scene may be determined based on the metadata and/or image data. The classification and prioritization information may be metadata and may be used to automatically remove undesirable portions of the video, generate suggestions during editing or automatically generate summary video.
Abstract:
Systems, methods, and a computer readable medium for performing auto exposure (AE) techniques that are beneficial in variable lighting conditions—and particularly applicable to handheld and/or mobile videoconferencing applications—are disclosed herein. Handheld and/or mobile videoconferencing applications—unlike their fixed camera counterparts—are often exposed to a wide variety of rapidly changing lighting and scene conditions, and thus face a difficult trade-off between adjusting exposure parameter values too frequently or not frequently enough. In personal electronic devices executing such handheld and/or mobile videoconferencing applications, it may be desirable to: use a small, centered, and center-weighted exposure metering region; set a relatively low brightness target value; and adjust the camera's exposure parameter values according to a distance-dependent convergence speed function. The use of such techniques, in conjunction with a relatively large stability region, may also improve the quality of a video encoder's temporal predictions—and thus video quality—in videoconferencing applications.