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A Visual-Based Dual-Target Tracking System Using Independent Component Analysis

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Detection and tracking of moving targets are major issues in visual surveillance and mobile robot navigation. However, segmentation of moving targets from background in a dynamic scene is still a challenging problem. Independent component analysis is a powerful statistical method for separating unknown signal sources from their linear mixtures into statistically independent components without prior knowledge. Recently, independent component analysis technique has also been successfully used in feature extraction and image segmentation. In this paper, we use the independent component analysis method to extract moving targets from complex background for development of a visual-based dual-target tracking system. The system incorporates two image tracking platforms and each consists of two cameras with two rotational degrees of freedom. First, the independent component analysis method is used for separating moving targets from complex background in a real-time video sequence. Next, after some image processing operations, we can calculate the centroid of detected moving targets in images, meanwhile, the relative position between moving targets and cameras can be estimated. Finally, with converting the relative position into actuating signals for driving motors, the two tracking platforms can track their own moving target and keep it in the middle of the surveillance image. Experimental results show that the proposed system works well for auto-tracking two walking persons in a surveillance zone.
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Document Type: Research Article

Publication date: 2012-05-01

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