Name
Abstract | ||
|---|---|---|
Recent years have seen tremendous progress in human detection, whereas only upright poses are usually considered. In this paper, we relax this constraint to localizing highly deformable persons, as commonly exhibited in personal photo albums. Human localization based on arbitrary pose is extremely challenging, due to the large pose variances, disabling the traditional part based template detectors. To tackle this issue, we propose a decomposition-based human localization model dealing with this issue in three-step: a stable upper-body is firstly detected, then a set of bigger bounding boxes are extended, from which the most appropriate instance is distinguished by a discriminative Whole Person Model. The experiment results demonstrated that our decomposition-based model worked very well at localizing deformable persons, which boosted the average precision by 10% compared to state-of-the-art person detectors. On the other hand, Similar Pose Feature(SPF) provides the feasibility of projecting persons with similar poses into same clusters, facilitating a novel pose-based photo album browsing functionality. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/VCIP.2013.6706345 | 2013 IEEE INTERNATIONAL CONFERENCE ON VISUAL COMMUNICATIONS AND IMAGE PROCESSING (IEEE VCIP 2013) |
Keywords | Field | DocType |
human detection, similar pose search | Computer vision,Object detection,Computer science,Image processing,Image retrieval,3D pose estimation,Visual communication,Artificial intelligence,Discriminative model,Bounding overwatch | Conference |
Volume | Issue | Citations |
null | null | 0 |
PageRank | References | Authors |
0.34 | 14 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bing Shuai | 1 | 3 | 1.06 |
| Song-zhi Su | 2 | 61 | 8.53 |
| Shaozi Li | 3 | 403 | 54.27 |
| Yun Cheng | 4 | 142 | 14.62 |
| Rongrong Ji | 5 | 3616 | 189.98 |