Paper
24 August 2006 An experimental comparison of block matching techniques for detection of moving objects
Author Affiliations +
Abstract
The detection of moving objects in complex scenes is the basis of many applications in surveillance, event detection, and tracking. Complex scenes are difficult to analyze due to camera noise and lighting conditions. Currently, moving objects are detected primarily using background subtraction algorithms, with block matching techniques as an alternative. In this paper, we complement our earlier work on the comparison of background subtraction methods by performing a similar study of block matching techniques. Block matching techniques first divide a frame of a video into blocks and then determine where each block has moved from in the preceding frame. These techniques are composed of three main components: block determination, which specifies the blocks; search methods, which specify where to look for a match; and, the matching criteria, which determine when a good match has been found. In our study, we compare various options for each component using publicly available video sequences of a traffic intersection taken under different traffic and weather conditions. Our results indicate that a simple block determination approach is significantly faster with minimum performance reduction, the three step search method detects more moving objects, and the mean-squared-difference matching criteria provides the best performance overall.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Nicole S. Love and Chandrika Kamath "An experimental comparison of block matching techniques for detection of moving objects", Proc. SPIE 6312, Applications of Digital Image Processing XXIX, 63120C (24 August 2006); https://doi.org/10.1117/12.680626
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CITATIONS
Cited by 1 scholarly publication and 2 patents.
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KEYWORDS
Fiber optic gyroscopes

Video

Light sources and illumination

Video surveillance

Cameras

Motion detection

Detection and tracking algorithms

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