Accelerated Event-Based Feature Detection and Compression for Surveillance Video Systems

The strong temporal consistency of surveillance video enables compelling compression performance with traditional methods, but downstream vision applications operate on decoded image frames with a high data rate. Since it is not straightforward for applications to extract information on temporal redundancy from the compressed video representations, we propose a novel system which conveys temporal redundancy within a sparse decompressed representation. We leverage a video representation framework called ADDER to transcode framed videos to sparse, asynchronous intensity samples. We introduce mechanisms …

applications compression cs.cv cs.mm data detection event extract feature image information novel performance rate redundancy surveillance systems temporal video vision