Institutional Repository
| Real-time and robust hand tracking with a single depth camera | |
| Ma, Ziyang (1); Wu, Enhua (1); Ma, Z.(maziyang08@gmail.com) | |
| 2013 | |
| Source | Visual Computer
 |
| ISSN | 1782789 |
| Volume | 30Issue:10Pages:1-12 |
| English Abstract | In this paper, we introduce a novel, real-time and robust hand tracking system, capable of tracking the articulated hand motion in full degrees of freedom (DOF) using a single depth camera. Unlike most previous systems, our system is able to initialize and recover from tracking loss automatically. This is achieved through an efficient two-stage k-nearest neighbor database searching method proposed in the paper. It is effective for searching from a pre-rendered database of small hand depth images, designed to provide good initial guesses for model based tracking. We also propose a robust objective function, and improve the Particle Swarm Optimization algorithm with a resampling based strategy in model based tracking. It provides continuous solutions in full DOF hand motion space more efficiently than previous methods. Our system runs at 40 fps on a GeForce GTX 580 GPU and experimental results show that the system outperforms the state-of-the-art model based hand tracking systems in terms of both speed and accuracy. The work result is of significance to various applications in the field of human-computer-interaction and virtual reality. © 2013 Springer-Verlag Berlin Heidelberg.; In this paper, we introduce a novel, real-time and robust hand tracking system, capable of tracking the articulated hand motion in full degrees of freedom (DOF) using a single depth camera. Unlike most previous systems, our system is able to initialize and recover from tracking loss automatically. This is achieved through an efficient two-stage k-nearest neighbor database searching method proposed in the paper. It is effective for searching from a pre-rendered database of small hand depth images, designed to provide good initial guesses for model based tracking. We also propose a robust objective function, and improve the Particle Swarm Optimization algorithm with a resampling based strategy in model based tracking. It provides continuous solutions in full DOF hand motion space more efficiently than previous methods. Our system runs at 40 fps on a GeForce GTX 580 GPU and experimental results show that the system outperforms the state-of-the-art model based hand tracking systems in terms of both speed and accuracy. The work result is of significance to various applications in the field of human-computer-interaction and virtual reality. © 2013 Springer-Verlag Berlin Heidelberg. |
| Indexed Type | SCI ; EI |
| Keyword | Hand Tracking Virtual Reality Motion Capture User Interface 3d Interaction |
| Department | (1) State Key Laboratory of Computer Science, Institute of Software, Chinese Academic of Sciences, Beijing, China; (2) University of Chinese Academy of Sciences, Beijing, China; (3) University of Macau, Macau, China |
| Language | 英语 |
| WOS ID | WOS:000342193800007 |
| Citation statistics | |
| Content Type | 期刊论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/16814 |
| Collection | 中国科学院软件研究所 |
| Corresponding Author | Ma, Z.(maziyang08@gmail.com) |
| Recommended Citation GB/T 7714 | Ma, Ziyang ,Wu, Enhua ,Ma, Z.. Real-time and robust hand tracking with a single depth camera[J]. Visual Computer,2013,30(10):1-12. |
| APA | Ma, Ziyang ,Wu, Enhua ,&Ma, Z..(2013).Real-time and robust hand tracking with a single depth camera.Visual Computer,30(10),1-12. |
| MLA | Ma, Ziyang ,et al."Real-time and robust hand tracking with a single depth camera".Visual Computer 30.10(2013):1-12. |
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