OCCLUSION ROBUST TRACKING OF MULTIPLE OBJECTS

被引：0

作者：

Lanz, Oswald ^{[1
]}

机构：

[1] ITC Irst, I-38100 Povo, TN, Italy

来源：

COMPUTER VISION AND GRAPHICS (ICCVG 2004) | 2006年 / 32卷

关键词：

Multiple Object Tracking; Occlusions; Bayes Filter; Particle Filter;

D O I：

10.1007/1-4020-4179-9_103

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper focuses on the problem of vision-based tracking of multiple objects. Probabilistic tracking in 3D supported by multiple video streams allows us to formalize an efficient observation model that is robust to occlusions. Each tracked object is assigned a support layer, a probabilistically meaningful pixel occupancy map, supplying weights used in the calculation of other objects observation likelihood. A Particle Filter implementation demonstrates the robustness of the resulting tracking system on synthetic data.

引用

页码：715 / 720

页数：6