Robust Visual Tracking Based on Simplified Biologically Inspired Features

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	Robust Visual Tracking Based on Simplified Biologically Inspired Features
	Min Li; Zhaoxiang Zhang; Kaiqi Huang; Tieniu Tan
	2009-11-07
会议日期	7-10 November 2009
会议地点	Cairo, Egypt
关键词	Robustness Target Tracking Biological System Modeling Bayesian Methods Particle Tracking Sampling Methods Particle Filters Inference Algorithms Lighting Immune System
页码	4113-4116
英文摘要	We address the problem of robust appearance-based visual tracking. First, a set of simplified biologically inspired features (SBIF) is proposed for object representation and the Bhattacharyya coefficient is used to measure the similarity between the target model and candidate targets. Then, the proposed appearance model is combined into a Bayesian state inference tracking framework utilizing the SIR (sampling importance resampling) particle filter to propagate sample distributions over time. Numerous experiments are conducted and experimental results demonstrate that our algorithm is robust to partial occlusions and variations of illumination and pose, resistent to nearby distractors, as well as possesses the state-of-the-art tracking accuracy.
会议录	IEEE International Conference on Image Processing, 2009
语种	英语
内容类型	会议论文
源URL	[http://ir.ia.ac.cn/handle/173211/12703]
专题	自动化研究所_智能感知与计算研究中心
通讯作者	Min Li
推荐引用方式 GB/T 7714	Min Li,Zhaoxiang Zhang,Kaiqi Huang,et al. Robust Visual Tracking Based on Simplified Biologically Inspired Features[C]. 见:. Cairo, Egypt. 7-10 November 2009.