A fast moving object detection method via local neighborhood similarity

Background subtraction is widely used in moving object detection. Pixel-based methods are sensitive to the nonstationary change of the scenes. Region-based approaches allow only coarse detection of the moving objects. In this paper, a novel algorithm based on local neighborhood similarity is propose...

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Bibliographic Details
Main Authors: Wei Li, Kaipeng Yang, Jiaxin Chen, Qingtao Wu, Mingchuan Zhang
Format: Conference Proceeding
Language:English
Subjects:
Automation
Background subtraction
Change detection algorithms
Educational institutions
Layout
Local Neighborhood Similarity
Mechatronics
Moving targets detection
Object detection
Pixel
Shape
Streaming media
Target recognition
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Summary:Background subtraction is widely used in moving object detection. Pixel-based methods are sensitive to the nonstationary change of the scenes. Region-based approaches allow only coarse detection of the moving objects. In this paper, a novel algorithm based on local neighborhood similarity is proposed. Integrate the similarity of its surrounding pixels with the background model, when a pixel needs to be judged. The performance of the proposed method is evaluated by a series of indoor and outdoor experiments. Compared with the current widely used Mixture of Gaussian, the proposed algorithm in this paper achieved the perfect results in object detection and extraction.
ISSN:2152-7431
2152-744X
DOI:10.1109/ICMA.2009.5244841