CNN implementation of a moving object segmentation approach for real-time video surveillance

In this paper we propose a CNN implementation of an algorithm for moving object segmentation intended for video surveillance applications. The approach is based on the comparison between the current frame and a background dynamically constructed from previous frames. The proposal includes capabiliti...

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Bibliographic Details
Published in2008 11th International Workshop on Cellular Neural Networks and Their Applications pp. 129 - 134
Main Authors Rodriguez-Fernandez, D., Vilarino, D.L., Pardo, X.M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2008
Subjects
Computer vision
History
Lighting
Noise
Object detection
Parallel processing
Pixel
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ISBN142442089X
9781424420896
ISSN2165-0144
DOI10.1109/CNNA.2008.4588664

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Summary:In this paper we propose a CNN implementation of an algorithm for moving object segmentation intended for video surveillance applications. The approach is based on the comparison between the current frame and a background dynamically constructed from previous frames. The proposal includes capabilities to detect changes in the illumination conditions as well as to alert against abandoned objects in the control area. The algorithm is composed by simple convolutions and morphological operations as well as simple arithmetic and logic operations which allow the implementation on current focal-plane cellular processor arrays.
ISBN:142442089X
9781424420896
ISSN:2165-0144
DOI:10.1109/CNNA.2008.4588664