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Vol. 177, Issue 8, August 2014, pp. 279-285

 

Bullet

 

A Novel Object Based Visual Tracking
 

1 Gaofeng Li, 1, 2 Wang Lei, 1 Peilong Li

1 School of Electronics and Information Engineering, Tongji University, Shanghai, 201804, China
2 Chinesisch-Deutsches Hochschulkolleg, Tongji University, Shanghai, 201804, China
1 Tel.: +86-182-0195-9628, fax: +86-021-6598-0860

1 E-mail: 2011gaofengli@tongji.edu.cn

 

Received: 8 August 2014 /Accepted: 29 August 2014 /Published: 31 August 2014

Digital Sensors and Sensor Sysstems

 

Abstract: Visual tracking is a challenging task for object with changing appearance in complex scenes. Online learning and detection trackers are developed to resolve the difficulties such as non-rigid, fast motion, occlusion, rotation and scale change. We propose a novel object based tracking method to achieve robust and accurate object. The integrity of object and structural parts are combined for object tracking. Compressive sensing is employed to represent object as root filter. The sparsity of measurement matrix is constrained with superpixel segmentation. The part-based model is adopted to filter the local invariant features of parts. The structural constraint strategy between parts and object is developed for adaptive tracking. We test our proposed algorithm on challenging sequences in real world and make qualitative and quantitative analysis. The experimental results demonstrate the method runs in real time and performs well comparable to state-of-the-art tracking.

 

Keywords: Compressive sensing, Part-based model, Super pixels, Structural constraints.

 

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