In this paper, we propose a visual tracking algorithm by incorporating the appearance information gathered from two collaborative feature sets and exploiting its geometric structures. A structured visual dictionary (SVD) can be learned from both appearance and geometric structure, thereby enhancing its discriminative strength between the foreground object and the background. Experimental results show that the proposed tracking algorithm using SVD (SVDTrack) performs favorably against the state-of-the-art methods.
Code and DatasetsThe MATLAB implementation can be downloaded from here (version 1.1). Please see README for more details.
Datasets to be uploaded.
Learning Structured Visual Dictionary for Object Tracking
Fan Yang, Huchuan Lu and Ming-Hsuan Yang
Image and Vision Computing (IVC), vol. 31, no. 12, pp. 992-999, 2013.