Name
Abstract | ||
|---|---|---|
For visual tracking, an ideal filter learned by the correlation filter (CF) method should take both discrimination and reliability information. However, existing attempts usually focus on the former one while pay less attention to reliability learning. This may make the learned filter be dominated by the unexpected salient regions on the feature map, thereby resulting in model degradation. To address this issue, we propose a novel CF-based optimization problem to jointly model the discrimination and reliability information. First, we treat the filter as the element-wise product of a base filter and a reliability term. The base filter is aimed to learn the discrimination information between the target and backgrounds, and the reliability term encourages the final filter to focus on more reliable regions. Second, we introduce a local response consistency regular term to emphasize equal contributions of different regions and avoid the tracker being dominated by unreliable regions. The proposed optimization problem can be solved using the alternating direction method and speeded up in the Fourier domain. We conduct extensive experiments on the OTB-2013, OTB-2015 and VOT-2016 datasets to evaluate the proposed tracker. Experimental results show that our tracker performs favorably against other state-of-the-art trackers. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/CVPR.2018.00058 | 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition |
Keywords | DocType | Volume |
element-wise product,unreliable regions,local response consistency regular term,reliable regions,final filter,discrimination information,reliability term,base filter,novel CF-based optimization problem,model degradation,unexpected salient regions,reliability information,correlation filter method,ideal filter,visual tracking,reliability learning,joint discrimination,correlation tracking | Conference | abs/1804.08965 |
ISSN | ISBN | Citations |
1063-6919 | 978-1-5386-6421-6 | 11 |
PageRank | References | Authors |
0.52 | 16 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chong Sun | 1 | 60 | 3.78 |
| Dong Wang | 2 | 326 | 14.06 |
| Huchuan Lu | 3 | 4827 | 186.26 |
| Yang Ming-Hsuan | 4 | 15303 | 620.69 |