EFFECTIVE APPEARANCE MODEL FOR PROBABILISTIC OBJECT TRACKING  

作　　者：Wang Shupeng Ji Hongbing 

机构地区：[1]School of Electronic Engineering, Xidian University, Xi＇an 710071, China [2]School of Communication and Information Engineering, Xi＇an University of Science and Technology, Xi＇an 7100541 China

出　　处：《Journal of Electronics(China)》2009年第4期503-508,共6页电子科学学刊（英文版）

基　　金：Supported by the National Natural Science Foundation of China (No. 60677040)

摘　　要：This paper presents a robust object tracking approach via a spatially constrained colour model. Local image patches of the object and spatial relation between these patches are informative and stable during object tracking. So, we propose to partition an object into patches and develop a Spatially Constrained Colour Model (SCCM) by combining the colour distributions and spatial configuration of these patches. The likelihood of the candidate object is given by estimating the confidences of the pixels in the candidate object region. The appearance model is learnt from the first frame and the tracking is carried out by particle filter. The experimental results show that the proposed tracking approach can accurately track the object with scale changes, pose variance and partial occlusion.This paper presents a robust object tracking approach via a spatially constrained colour model. Local image patches of the object and spatial relation between these patches are informative and stable during object tracking. So, we propose to partition an object into patches and develop a Spatially Constrained Colour Model （SCCM） by combining the colour distributions and spatial configuration of these patches. The likelihood of the candidate object is given by estimating the confidences of the pixels in the candidate object region. The appearance model is learnt from the first frame and the tracking is carried out by particle filter. The experimental results show that the proposed tracking approach can accurately track the object with scale changes, pose variance and partial occlusion.

关 键 词：Object tracking Appearance model Particle filter Adaptive scale 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TN953[自动化与计算机技术—计算机科学与技术]