Title: Real-time and robust hand tracking with a single depth camera
Author: Ma, Ziyang (1)
; Wu, Enhua (1)
Corresponding Author: Ma, Z.(maziyang08@gmail.com)
Keyword: Hand tracking
; Virtual reality
; Motion capture
; User interface
; 3D interaction
Source: Visual Computer
Issued Date: 2013
Volume: 30, Issue: 10, Pages: 1-12 Indexed Type: SCI
; EI
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
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. 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. Language: 英语
WOS ID: WOS:000342193800007
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Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/16814
Appears in Collections: 软件所图书馆_期刊论文
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Recommended Citation:
Ma, Ziyang ,Wu, Enhua . Real-time and robust hand tracking with a single depth camera[J]. Visual Computer,2013-01-01,30(10):1-12.
