Name
Abstract | ||
|---|---|---|
In this study, we propose a new integrated computer vision system designed to track multiple human beings and extract their silhouette with a pan-tilt stereo camera, so that it can assist in gesture and gait recognition in the field of Human–Robot Interaction (HRI). The proposed system consists of three modules: detection, tracking and silhouette extraction. These modules are robust to camera movements, and they work interactively in near real-time. Detection was performed by camera ego-motion compensation and disparity segmentation. For tracking, we present an efficient mean shift-based tracking method in which the tracking objects are characterized as disparity weighted color histograms. The silhouette was obtained by two-step segmentation. A trimap was estimated in advance and then effectively incorporated into the graph-cut framework for fine segmentation. The proposed system was evaluated with respect to ground truth data, and it was shown to detect and track multiple people very well and also produce high-quality silhouettes. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/s10044-008-0112-3 | Pattern Anal. Appl. |
Keywords | Field | DocType |
robot visionhuman detectiontracking � silhouette extraction,disparity segmentation,silhouette extraction,fine segmentation,high-quality silhouette,robot interaction system,human tracking,camera movement,efficient mean shift-based tracking,camera ego-motion compensation,proposed system,tracking object,pan-tilt stereo camera,human robot interaction,mean shift,graph cut,computer vision,near real time,ground truth,system design,tracking,color histogram | Computer vision,Stereo camera,Pattern recognition,Silhouette,Segmentation,Motion compensation,Gesture recognition,Image segmentation,Artificial intelligence,Motion estimation,Mathematics,Human–robot interaction | Journal |
Volume | Issue | ISSN |
12 | 2 | 1433-755X |
Citations | PageRank | References |
8 | 0.63 | 47 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jung-Ho Ahn | 1 | 8 | 0.63 |
| Cheolmin Choi | 2 | 11 | 1.40 |
| Sooyeong Kwak | 3 | 39 | 5.65 |
| Kilcheon Kim | 4 | 23 | 2.81 |
| Hyeran Byun | 5 | 505 | 65.97 |