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Robust Visual Tracking Based on Simplified Biologically Inspired Features
Min Li; Zhaoxiang Zhang; Kaiqi Huang; Tieniu Tan
Conference Name16th IEEE International Conference on Image Processing
Source PublicationIEEE International Conference on Image Processing, 2009
Conference Date7-10 November 2009
Conference PlaceCairo, Egypt
AbstractWe 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.
KeywordRobustness Target Tracking Biological System Modeling Bayesian Methods Particle Tracking Sampling Methods Particle Filters Inference Algorithms Lighting Immune System
Document Type会议论文
Corresponding AuthorMin Li
Recommended Citation
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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