Abstract: A computerized system and method may provide a dynamic, adaptable, and robust framework for intelligent web-based video playing. A computerized system including a memory and a computer processor may arrange a plurality of video frames based on one or more data items associated with groups of pictures (GOPs) and/or video playing commands and/or settings, and render and/or play the arranged frames on an output display. Functionalities enabled by different embodiments of the invention include, for example: automatically adjusting a video playing speed according to a number of accumulated frames within a memory buffer; appending a memory buffer with frames included in another (e.g., separate) memory buffer based on a requested video playing direction; omitting frames from a video sequence (thus sparing the need to process omitted frames) based on quantifying their information content and/or distance from reference frames; and synchronizing video playing on different (e.g., remote) computer systems.

Abstract: A system and method for dynamically ordering video streams on display in a command and control system according to video content, including obtaining a plurality of video streams captured by a plurality of respective video cameras; extracting features from the plurality of video streams; calculating abnormality scores for the extracted features, wherein each abnormality score measures a likelihood that a corresponding feature is an abnormal feature; calculating a current rank for ordering each of the plurality of video streams based on current and past abnormality scores of the features extracted from the video stream; and displaying a subgroup of the plurality of video streams having the highest subset of current ranks based on abnormality scores.

Abstract: A system and method for dynamically ordering video streams on display in a command and control system according to video content, including obtaining a plurality of video streams captured by a plurality of respective video cameras; extracting features from the plurality of video streams; calculating abnormality scores for the extracted features, wherein each abnormality score measures a likelihood that a corresponding feature is an abnormal feature; calculating a current rank for ordering each of the plurality of video streams based on current and past abnormality scores of the features extracted from the video stream; and displaying a subgroup of the plurality of video streams having the highest subset of current ranks based on abnormality scores.

Abstract: A system and method for dynamically ordering video streams on display in a command and control system according to video content, including obtaining a plurality of video streams captured by a plurality of respective video cameras; extracting features from the plurality of video streams; calculating abnormality scores for the extracted features, wherein each abnormality score measures a likelihood that a corresponding feature is an abnormal feature; calculating a current rank for ordering each of the plurality of video streams based on current and past abnormality scores of the features extracted from the video stream; and displaying a subgroup of the plurality of video streams having the highest subset of current ranks based on abnormality scores.

Abstract: A system and method for dynamically ordering video streams on display in a command and control system according to video content, including obtaining a plurality of video streams captured by a plurality of respective video cameras; extracting features from the plurality of video streams; calculating abnormality scores for the extracted features, wherein each abnormality score measures a likelihood that a corresponding feature is an abnormal feature; calculating a current rank for ordering each of the plurality of video streams based on current and past abnormality scores of the features extracted from the video stream; and displaying a subgroup of the plurality of video streams having the highest subset of current ranks based on abnormality scores.

Abstract: A system and method for estimating an expected waiting time for a person entering a queue may receive image data captured from at least one image capture device during a period of time prior to the person entering the queue; calculate, based on the image data, one or more prior waiting time estimations, a queue handling time estimation, and a queue occupancy; assign a module weight to each of the one or more prior waiting time estimations and to the queue handling time estimation; generate, based on at least the calculations of the one or more prior waiting time estimations, the queue handling time estimation, and the respective module weights, a recent average handling time for the prior period of time; and determine the expected waiting time based on the recent average handling time and the queue occupancy.