【摘要】 讨论了非线性非高斯假设条件下视频追踪的问题和时序蒙特卡罗技术的最新发展,尤其是粒子滤波算法的发展,使采用一个目标状态的集合对贝叶斯模型的后验分布进行建模和跟踪成为可能,这个集合可以看作是这个后验密度函数的采样集合.提出的算法考虑了衰减问题及重复采样,实验结果表明,该方法能清晰稳定地进行视频追踪.更多还原

【Abstract】 The problem of visual tracking under non-Gaussian and non-linear assumption is addressed.Recent advances in sequential Monte Carlo techniques,especifically in particle filter algorithm,allow us to model and track the posterior distribution defined by Bayesian model using a collection of targets states.That collection can be viewed as samples from the posterior of interest.The proposed algorithm takes the degeneracy problem and resampling into consideration.Experimental results show that our approach can yield robust and stable tracking performance.更多还原