Video target tracking by using competitive neural networks
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Abstract
A target tracking algorithm able to identify the position and to pursuit moving targets in video digital sequences is proposed in this paper. The proposed approach aims to track moving targets inside the vision field of a digital camera. The position and trajectory of the target are identified by using a neural network presenting competitive learning technique. The winning neuron is trained to approximate to the target and, then, pursuit it. A digital camera provides a sequence of images and the algorithm process those frames in real time tracking the moving target. The algorithm is performed both with black and white and multi-colored images to simulate real world situations. Results show the effectiveness of the proposed algorithm, since the neurons tracked the moving targets even if there is no pre-processing image analysis. Single and multiple moving targets are followed in real time.
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Keywords
Computational intelligence, Image motion, Neural network, Target tracking, Video digital camera, Artificial intelligence, Cameras, Computer graphics, Digital cameras, Image analysis, Image enhancement, Intelligent control, Learning algorithms, Targets, Tracking (position), Vegetation, Video cameras, Colored images, Competitive learnings, Competitive neural networks, Digital sequences, Moving targets, Pre-processing, Real times, Real worlds, Sequence of images, Tracking algorithms, Video target tracking, Winning neurons, Neural networks
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English
Citation
WSEAS Transactions on Signal Processing, v. 4, n. 8, p. 420-431, 2008.
