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Robust Visual Tracking Based on Simplified Biologically Inspired Features
Min Li; Zhaoxiang Zhang; Kaiqi Huang; Tieniu Tan
2009-11-07
会议名称16th IEEE International Conference on Image Processing
会议录名称IEEE International Conference on Image Processing, 2009
页码4113-4116
会议日期7-10 November 2009
会议地点Cairo, Egypt
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.
关键词Robustness Target Tracking Biological System Modeling Bayesian Methods Particle Tracking Sampling Methods Particle Filters Inference Algorithms Lighting Immune System
语种英语
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/12703
专题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],2009:4113-4116.
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