abstract

• Motion Detection is major task in every application of computer vision such as video surveillance. Background Subtraction (BS) algorithms have been employed for several years to find a moving objects in a scene. BS has been used in video surveillance due to its simplicity and the fact that cameras are stationary in a video surveillance systems. The present paper introduce a new approach to motion detection through a hierarchical model that uses Mutual Information as a measure of change in the scene. Since pixels in a frame belong to objects, a segmentation in regions of the frame is done by mean-shift algorithm. Then a Mutual information measurement between the segmented region and the incoming frame is performed. A first approach to foreground mask is achieved and later is refined using a modification of the Wronskian Change Detector (WCD). The experimental results show that our proposed algorithm improve the performance in comparison with a pixel based Background Subtraction algorithm mixture of gaussians (MoG), a hierarchical block based Background Subtraction algorithm (HMDRP) and a test of linear independence (WCD). © 2016 IEEE.

authors

• Aguilar Ponce Ruth Mariela
• Gamboa-Aispuro J.M.
• Tecpanecatl Xihuitl José Luis

publication date

• 2017-01-01

published in

• 2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016  Proceedings

keywords

• Hierarchical systems; Image segmentation; Monitoring; Motion analysis; Motion compensation; Pixels; Background subtraction; Background subtraction algorithms; Hierarchical model; Linear independence; Mean shift algorithm; Mixture of gaussians (MOG); Mutual informations; Video surveillance systems; Security systems

Digital Object Identifier (DOI)

• 10.1109/ROPEC.2016.7830582

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