Name
Title | ||
|---|---|---|
Online structured sparse learning with labeled information for robust object tracking. |
Abstract | ||
|---|---|---|
We formulate object tracking under the particle filter framework as a collaborative tracking problem. The priori information from training data is exploited effectively to online learn a discriminative and reconstructive dictionary, simultaneously without losing structural information. Specifically, the class label and the semantic structure information are incorporated into the dictionary learning process as the classification error term and ideal coding regularization term, respectively. Combined with the traditional reconstruction error, a unified dictionary learning framework for robust object tracking is constructed. By minimizing the unified objective function with different mixed norm constraints on sparse coefficients, two robust optimizing methods are developed to learn the high-quality dictionary and optimal classifier simultaneously. The best candidate is selected by minimizing the reconstructive error and classification error jointly. As the tracking continues, the proposed algorithms alternate between the robust sparse coding and the dictionary updating. The proposed trackers are empirically compared with 14 state-of-the-art trackers on some challenging video sequences. Both quantitative and qualitative comparisons demonstrate that the proposed algorithms perform well in terms of accuracy and robustness. (C) 2017 SPIE and IS& T |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1117/1.JEI.26.1.013007 | JOURNAL OF ELECTRONIC IMAGING |
Keywords | Field | DocType |
robust object tracking,online dictionary learning and updating,robust sparse coding,prior information,joint decision metric | K-SVD,Computer science,Particle filter,Robustness (computer science),Coding (social sciences),Artificial intelligence,Discriminative model,Computer vision,Pattern recognition,Neural coding,Video tracking,Associative array,Machine learning | Journal |
Volume | Issue | ISSN |
26 | 1 | 1017-9909 |
Citations | PageRank | References |
2 | 0.37 | 27 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Baojie Fan | 1 | 41 | 10.48 |
| Yang Cong | 2 | 684 | 38.22 |
| Y. Tang | 3 | 243 | 33.69 |