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2009
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Corner-based Background Segmentation Using Adaptive Resonance Theory

10 years 11 months ago
Corner-based Background Segmentation Using Adaptive Resonance Theory
A correct video segmentation, namely the detection of moving objects within a scene plays a very important role in many application in safety, surveillance, trafic monitoring and object detection. The main objective of this paper is to implement an effective background segmentation algorithm for corner sets extracted from video sequences. A dynamic prototype of the structure of background corners is produced and incoming corners are classified using a Fuzzy ARTMAP Neural Network and labeled as pertaining to the background or foreground using a spatial clustering method. Finally the accuracy of the proposed algorithm is evaluated using PETS2006 benchmark data.
Added 10 Nov 2009
Updated 26 Dec 2009
Type Conference
Year 2009
Where ICIP
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