3D hand tracking using Kalman filter in depth space

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• 作者：Sangheon Park (1)
  Sunjin Yu (2)
  Joongrock Kim (1)
  Sungjin Kim (2)
  Sangyoun Lee (1)
  
• 关键词：hand detection ; hand tracking ; depth information
• 刊名：EURASIP Journal on Advances in Signal Processing
• 出版年：2012
• 出版时间：December 2012
• 年：2012
• 卷：2012
• 期：1
• 全文大小：1939KB
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• 作者单位：Sangheon Park (1)
  Sunjin Yu (2)
  Joongrock Kim (1)
  Sungjin Kim (2)
  Sangyoun Lee (1)
  
  1. Department of Electrical and Electronic Engineering, Yonsei University, 134 Shinchon-Dong, Seodaemun-Gu, Seoul, Korea
  2. Future IT Convergence Lab, LG Electronics Advanced Research Institute, 221, Yangjae-Dong, Seocho-Gu, Seoul, Korea
  
• ISSN：1687-6180

文摘

Hand gestures are an important type of natural language used in many research areas such as human-computer interaction and computer vision. Hand gestures recognition requires the prior determination of the hand position through detection and tracking. One of the most efficient strategies for hand tracking is to use 2D visual information such as color and shape. However, visual-sensor-based hand tracking methods are very sensitive when tracking is performed under variable light conditions. Also, as hand movements are made in 3D space, the recognition performance of hand gestures using 2D information is inherently limited. In this article, we propose a novel real-time 3D hand tracking method in depth space using a 3D depth sensor and employing Kalman filter. We detect hand candidates using motion clusters and predefined wave motion, and track hand locations using Kalman filter. To verify the effectiveness of the proposed method, we compare the performance of the proposed method with the visual-based method. Experimental results show that the performance of the proposed method out performs visual-based method.