Fast Object Tracking in Compressed Videos for Real Time Surveillance
نویسندگان
چکیده
Video analysis for object tracking has a strong demand due to the proliferation of surveillance video applications. This paper presents a novel low complexity and reliable multi-object tracking algorithm that uses the motion vectors directly from the coder by an optimal adaptation error optimization. Such a tracking scheme is very suitable for the surveillance and real time video analysis applications. The proposed method is applied on H.264/AVC scalable layered structured videos known as SVC with different spatial and temporal resolutions. Results depict that in such a compressed nature of videos, reduction of additional computation and complexity significantly improve the tracking efficiency.
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تاریخ انتشار 2014