Abstract: Various examples are directed to systems and methods for detecting regions in video frames. For example, a computing device may receive a video comprising a plurality of frames and a video frame sequence of the plurality of frames. The computing device may select a plurality of scene point location from a first frame. The computing device may determine a plurality of columns in the first frame and fit a first sinusoidal function to a distribution of average column Y-axis displacements for the plurality of columns by column position. The computing device may determine a first difference based at least in part on the first scene point Y-axis displacement and an output of the first sinusoidal function at the X-axis position of the first scene point and determine that the first difference is greater than a threshold distance.

Abstract: Various examples are directed to systems and methods for determining foreground regions in video frames. A computing device may select from a first frame of a video, a plurality of scene point locations and divide the first frame into a plurality of sections. For a first section of the first frame, the computing device may generate a first vector subspace, basis vectors of the first vector subspace are trajectories of scene point locations in the first section. The computing device may determine that a projection error for a first scene point location in the first section is greater than a projection error threshold and write an indication of the first pixel value to a listing of foreground pixel values.

Abstract: A system and method for selecting portions of video data from preview video data is provided. The system may extract image features from the preview video data and discard video frames associated with poor image quality based on the image features. The system may determine similarity scores between individual video frames and corresponding transition costs and may identify transition points in the preview video data based on the similarity scores and/or transition costs. The system may select portions of the video data for further processing based on the transition points and the image features. By selecting portions of the video data, the system may reduce a bandwidth consumption, processing burden and/or latency associated with uploading the video data or performing further processing.

Abstract: A system determines what regions in a scene captured by a camera include highly reflective (specular) surfaces. The system illuminates the scene by outputting images to a display screen such as a television screen so as to illuminate the scene from different angles. Images of the scene are captured by the camera under the different illuminations. The images are analyzed to determine which regions in the scene exhibit changes in reflected luminance that correspond to the changes in illumination, indicating a specular surface. Regions containing diffuse surfaces are also identified based on such regions exhibiting a reflected luminance that is substantially independent of the changes in illumination.

Abstract: A system and method for generating preview data from video data and using the preview data to select portions of the video data or determine an order with which to upload the video data. The system may sample video data to generate sampled video data and may identify portions of the sampled video data having complexity metrics exceeding a threshold. The system may upload a first portion of the video data corresponding to the identified portions while omitting a second portion of the video data. The system may determine an order with which to upload portions of the video data based on a complexity of the video data. Therefore, portions of the video data that may require additional processing after being uploaded may be prioritized and uploaded first. As a result, a latency between the video data being uploaded and a video summarization being received is reduced.

Abstract: A system and method for generating preview data from video data and using the preview data to select portions of the video data or determine an order with which to upload the video data. The system may sample video data to generate sampled video data and may identify portions of the sampled video data having complexity metrics exceeding a threshold. The system may upload a first portion of the video data corresponding to the identified portions while omitting a second portion of the video data. The system may determine an order with which to upload portions of the video data based on a complexity of the video data. Therefore, portions of the video data that may require additional processing after being uploaded may be prioritized and uploaded first. As a result, a latency between the video data being uploaded and a video summarization being received is reduced.

Abstract: Methods, system, and apparatus for generating depth maps are described. A depth map may be generated by obtaining a transformation for a prism camera having a still image capture mode and a video mode (the transformation based on the difference between the still image transfer mode and the video mode), capturing a multi-view still image with the camera, capturing multi-view video images with the camera, and generating a resolved video depth map from the transformation, the multi-view still image, and the multi-view video. The depth map may be converted to a 3D structure. Multiple resolved 3D structures from prism camera apparatus may be combined to generate volumetric reconstruction of the scene.