Method and system for efficient sampling of videos using spatiotemporal constraints for statistical behavior analysis

An apparatus for storing selected video segments for a person or a plurality of persons that visited an area covered by a plurality of means for capturing images, comprising:

• a) a plurality of means for capturing images for capturing a plurality of video streams of the person or the plurality of persons in the area,
• b) at least a means for video interface that is connected to the plurality of means for capturing images,
• c) at least a computer that executes computer vision algorithms on the plurality of video streams, performing the following steps of:
• finding information for the trip of the person or the plurality of persons based on track sequences calculated from tracking the person or the plurality of persons in video streams,
• determining a first set of video segments that contain the trip information of the person or the plurality of persons and a second set of video segments that do not contain the trip information of the person or the plurality of persons in each of the video streams,
• removing the second set of video segments from each of the video streams,
• selecting video segments from the first set of video segments based on predefined selection criteria, applying multi-layered spatiotemporal constraints to select the video segments, for the statistical behavior analysis,
• applying domain-specific sampling criteria to the selection of video segments, and
• compacting each of the video streams using the first set of video segments, after removing the second set of video segments from each of the video streams.,
• d) at least a means for storing data that stores the selected video segments, and
• whereby the application of the multi-layered spatiotemporal constraints further reduces the size of the selected video segments.