|Robust Visual Tracking Based on Simplified Biologically Inspired Features|
|Min Li; Zhaoxiang Zhang; Kaiqi Huang; Tieniu Tan
|会议名称||16th IEEE International Conference on Image Processing
|会议录名称||IEEE International Conference on Image Processing, 2009
|会议日期||7-10 November 2009
|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.|
Biological System Modeling
Min Li,Zhaoxiang Zhang,Kaiqi Huang,et al. Robust Visual Tracking Based on Simplified Biologically Inspired Features[C],2009:4113-4116.