Abstract

Motion detection in pixel domain of videos often requires highly capable resource to perform. This is due to computational demands for decoding the videos to obtain visual image. The problem can be solved by performing motion detection directly on bit streams of the compressed video data. This paper presents a new method for moving object detection in compressed domain of high resolution surveillance videos. In this work, we use video coding parameters (eg. motion vectors) extracted directly from bit stream of the compressed video to separate the moving blocks out of video background. We then propose new techniques for the segmentation and refinement of the foreground blocks to detect the moving objects. Experiments have been conducted on both public and self-recorded video data sets. Experimental results show the outperformance of our proposed method in comparing with conventional one.

Keywords:
Computer science Computer vision Artificial intelligence Motion compensation Decoding methods Object detection Block-matching algorithm Video tracking Motion detection Segmentation Video compression picture types Motion estimation Video processing Coding (social sciences) Motion (physics) Algorithm Mathematics

Metrics

5
Cited By
0.00
FWCI (Field Weighted Citation Impact)
12
Refs
0.18
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Video Coding and Compression Technologies
Physical Sciences →  Computer Science →  Signal Processing
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Video Surveillance and Tracking Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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