Real-time and robust hand tracking with a single depth camera
文献类型：期刊论文
| 作者 | Ma, Ziyang (1) ; Wu, Enhua (1) |
| 刊名 | Visual Computer
 |
| 出版日期 | 2013 |
| 卷号 | 30期号:10页码:1-12 |
| 关键词 | Hand tracking Virtual reality Motion capture User interface 3D interaction |
| ISSN号 | 1782789 |
| 通讯作者 | Ma, Z.(maziyang08@gmail.com) |
| 中文摘要 | 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. |
| 英文摘要 | 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. |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:000342193800007 |
| 公开日期 | 2014-12-16 |
| 源URL | [http://ir.iscas.ac.cn/handle/311060/16814]  |
| 专题 | 软件研究所_软件所图书馆_期刊论文 |
| 推荐引用方式 GB/T 7714 | Ma, Ziyang ,Wu, Enhua . Real-time and robust hand tracking with a single depth camera[J]. Visual Computer,2013,30(10):1-12. |
| APA | Ma, Ziyang ,&Wu, Enhua .(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. |
入库方式： OAI收割
来源：软件研究所
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