Name
Title | ||
|---|---|---|
Visual tracking via multiple representative basic appearance models based on l 1 minimization |
Abstract | ||
|---|---|---|
Almost all the online tracking methods suffer from the problem of drift. The critical reason lies in that they only focus on how to get the most adaptive visual model to the last state(s), but lose the memory of the learned features. Aiming to address this challenging problem, we propose a novel appearance model within the framework of Bayesian-based tracking. The appearance model combines with the most representative basic models learned in the past temporal space. These basic representative appearance models, as the accumulated memory of the different aspects of features from different learning periods, can approximate the target appearance of the coming state as well as possible. Meanwhile, we design methods to online construct and update the basic models. Also, a dynamic scheme is employed to integrate the basic models. The novel model proposed in this paper, by explicit inference, can effectively and efficiently handle the challenging cases such as full occlusion, frequent and drastic appearance variation of the target. As well, it is demonstrated by the extensive experiments. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2401603.2401631 | RACS |
Keywords | Field | DocType |
adaptive visual model,representative basic model,basic model,multiple representative basic appearance,novel model,basic representative appearance model,appearance model,target appearance,drastic appearance variation,visual tracking,bayesian-based tracking,novel appearance model,sparse representation | Computer science,Inference,Sparse approximation,Active appearance model,Design methods,Eye tracking,Minification,Artificial intelligence,Machine learning,Bayesian probability | Conference |
Citations | PageRank | References |
1 | 0.37 | 9 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Deqian Fu | 1 | 7 | 4.51 |
| Seong Tae Jhang | 2 | 20 | 8.59 |