Mean shift blob tracking with kernel histogram filtering and hypothesis testing

@article{Peng2005MeanSB,
  title={Mean shift blob tracking with kernel histogram filtering and hypothesis testing},
  author={Ningsong Peng and Jie Yang and Zhi Liu},
  journal={Pattern Recognition Letters},
  year={2005},
  volume={26},
  pages={605-614}
}
We propose a new adaptive model update mechanism for the real-time mean shift blob tracking. Since the Kalman filter has been used mainly for smoothing the object trajectory in the tracking system, it is novel for us to use adaptive Kalman filters for filtering object kernel histogram so as to obtain the optimal estimate of object model. The acceptance of the object estimate for the next frame tracking is determined by a robust criterion, i.e. the result of hypothesis testing with the samples… CONTINUE READING
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