Video Tracking via Tensor Neighborhood Preserving Discriminant Embedding
In a real surveillance scenario,tracking an object usually interfered by the background information.To deal with this problem,this paper proposed a video tracking algorithm based on tensor neighborhood preserving discriminant embedding.The neighborhood relationships of an object within object class and background class are reasonable described by the object image patches similarities which are defined by histograms of oriented gradients.In order to distinguish between the object and background,we formulate an discriminant objective function that maximizing the scatters of object within object class while minimizing the scatters of object with background class,meanwhile maintaining the same neighborhood topological structure in lower dimensional tensor subspace.Finally,we can get the optimal estimate of the object state through Bayesian estimation framework.Experimental evaluations against two state-of-the-art tracking methods demonstrate the robustness and effectiveness of the proposed algorithm.
video tracking neighborhood preserving tensor Discriminant
Jiashu Dai Tingquan Deng Tianzhen Dong Kejia Yi
Laboratory of Fuzzy Information Analysis and Intelligent Recognition Harbin Engineering University H Science and Technology on Underwater Acoustic Antagonizing Laboratory Systems Engineering Research I
国际会议
西安
英文
245-248
2013-09-14（万方平台首次上网日期，不代表论文的发表时间）