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26 September 2013 Real-time object tracking with correlation filtering and state prediction
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Abstract
A real-time tracking system based on adaptive correlation filtering and state prediction is proposed. The system is able to estimate at high-rate the position of multiple targets within the observed scene by taking into account information of past and present scene-frames. The position of the targets in the current frame is estimated with the help of a bank of composite correlation filters applied to several small regions taken from the observed scene. These small regions are updated in each frame according to information from a state predictor based on the motion model of targets in a twodimensional plane. The proposed system is implemented on a graphics processing unit to take advantage of massive parallelism. Computer simulation results obtained with the proposed system are presented and discussed in terms of tracking accuracy and real-time operation efficiency.
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Viridiana Contreras, Victor H. Díaz-Ramírez, Vitaly Kober, and Juan J. Tapia-Armenta "Real-time object tracking with correlation filtering and state prediction", Proc. SPIE 8856, Applications of Digital Image Processing XXXVI, 885619 (26 September 2013); https://doi.org/10.1117/12.2024363
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