Real-Time Object Tracking Based on the Relative Hist Model within Particle Filter Framework

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 先进时空数据分析与学习

	Real-Time Object Tracking Based on the Relative Hist Model within Particle Filter Framework
	Wang, Lingfeng; Pan, Chunhong
	2010
会议名称	International Conference on Acoustics, Speech, and Signal Processing
会议录名称	International Conference on Acoustics, Speech, and Signal Processing
会议日期	2010
会议地点	Dallas, Texas, USA
摘要	This paper proposes a novel real-time tracking algorithm by using the relative hist model within particle filter framework. The target-region is roughly enclosed with a rectangle as usual, and color features are used to describe all the types of regions by calculating their color histograms. Inevitably, the background pixels are included in the target-region and the histogram of target-region may be corrupted when performing tracking algorithm. Even the target fails to track. Thus, the relative hist model is proposed to reduce the influence of background pixels. In this model, we not only consider the similarity between the candidate-region and target-region, but also consider the similarity between the candidate-region and background. In other words, the relative hist model tries to find a candidate-region which is more similar to the target-region but less similar to the background. By adopting this model, our tracking algorithm can accurately track the object in real-time. Experiments are performed in various tracking scenes. The experiment results show that our algorithm is of appealing with respect to robustness for real-time object tracking against various backgrounds.
关键词	Relative Hist Model Particle Filter
语种	英语
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/10767
专题	多模态人工智能系统全国重点实验室_先进时空数据分析与学习
作者单位	中国科学院自动化研究所
第一作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Wang, Lingfeng,Pan, Chunhong. Real-Time Object Tracking Based on the Relative Hist Model within Particle Filter Framework[C],2010.

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