|Robust Visual Tracking Based on Simplified Biologically Inspired Features|
|Min Li; Zhaoxiang Zhang; Kaiqi Huang; Tieniu Tan
|Conference Name||16th IEEE International Conference on Image Processing
|Source Publication||IEEE International Conference on Image Processing, 2009
|Conference Date||7-10 November 2009
|Conference Place||Cairo, Egypt
|Abstract||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
|Corresponding Author||Min Li|
Min Li,Zhaoxiang Zhang,Kaiqi Huang,et al. Robust Visual Tracking Based on Simplified Biologically Inspired Features[C],2009:4113-4116.
|Files in This Item:||
||There are no files associated with this item.
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.