Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/9941
Title: Binary histogram based split/merge object detection using FPGAs
Authors: Appiah, K
Meng, H
Hunter, A
Dickinson, P
Keywords: Tracking of objects;Colour histograms;Visual surveillance systems
Issue Date: 2010
Citation: Proceedings of IEEE Int’l Conf. Computer Vision and Pattern Recognition (CVPR-W’10), The Sixth IEEE Embedded Computer Vision Workshop, pp. 45 - 52, 2010
Abstract: Tracking of objects using colour histograms has proven successful in various visual surveillance systems. Such systems rely heavily on similarity matrices to compare the appearance of targets in successive frames. The computational cost of the similarity matrix is increased if proximate objects merge into a single object or a single object fragments into two or more parts. This paper presents a method of reducing this computational cost with the use of a reconfigurable computing architecture. Colour histogram data of moving targets are used to generate binary signatures for the detection of merged or fragmented objects. The main contribution in this paper is how binary histogram data is generated and used to detect split/merge object with the use of logical operations native to the hardware architecture used for its implementation. The results show a 10 fold improvement in processing speed over the microprocessor based implementation, and that it
URI: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5543760
http://bura.brunel.ac.uk/handle/2438/9941
DOI: http://dx.doi.org/10.1109/CVPRW.2010.5543760
Appears in Collections:Dept of Computer Science Research Papers

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