Abstract
In order to get a better solution on non-linear and non-Gaussian targets tracking problems, a novel multi-object tracking framework based on particle filter with data association is proposed. Firstly, a self-adaptive size tracking window algorithm is given and integrated into the tracking framework for the changes scale of moving objects, then a novel data association method based on JPDA is proposed, in which the tracking window, the observation data of the same object at adjacent frames and the different objects at the same frame are jointly associated to achieve accurate data association during tracking. The simulation results indicates that the proposed framework can be used effectively in multi-object tracking, it have the ability of dealing with the challenges such as object occlusion, separating, merging, and pot up.
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Li, P., Wang, Y. (2015). Object Tracking Based on Particle Filter with Data Association. In: Tan, T., Ruan, Q., Wang, S., Ma, H., Di, K. (eds) Advances in Image and Graphics Technologies. IGTA 2015. Communications in Computer and Information Science, vol 525. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-47791-5_13
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DOI: https://doi.org/10.1007/978-3-662-47791-5_13
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