Meanshift Blob Tracking with Target Model adaptive Update
An adaptive model update mechanism for mean shift tracking is proposed in this paper.Gaussian Model always has been used in background model estimation to realize object tracking.It is novel that each bins of kernel histogram is modeled as mixture of Gaussian and the on-line approximation used to update the model.Gaussian distributions are ordered based on the fitness value of weight and covariance.Object model is determined by each gaussian distributions and weight.Therefore the improved mean shift can not only update object model in time but also deal with object appearance changes and occlusion.Experiments demonstrate that the improved method can track objects under the changes of appearance and occlusion with satisfactory results.
Mean shift Gaussian model Gaussian mixture model Model update
ZHAO Yunji ZHANG Bin ZHANG Xinliang
School of Electrical Engineering and Automation,Henan Polytechnic University,Jiaozuo,Henan,454000,P. Henan Mechanical Electrical Vocational College,Zhengzhou,Henan,451191,P.R.China
国际会议
The 33th Chinese Control Conference第33届中国控制会议
南京
英文
4831-4835
2014-07-28（万方平台首次上网日期，不代表论文的发表时间）