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.
Video target tracking by using competitive neural networks
2008-12-01
2-s2.0-58249104081
Article (Journal)
Electronic Resource
English
Digital cameras , Real worlds , Colored images , Moving targets , Video digital camera , Winning neurons , Competitive neural networks , Vegetation , Artificial intelligence , Image enhancement , Image motion , Computational intelligence , Video target tracking , Competitive learnings , Real times , Neural networks , Sequence of images , Targets , Digital sequences , Video cameras , Tracking (position) , Neural network , Tracking algorithms , Computer graphics , Pre-processing , Target tracking , Learning algorithms , Cameras , Intelligent control , Image analysis
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