Hand Region Tracking and Fingertip Detection based on Depth Image

깊이 영상 기반 손 영역 추적 및 손 끝점 검출

  • 주성일 (숭실대학교 글로벌미디어학과) ;
  • 원선희 (숭실대학교 글로벌미디어학과) ;
  • 최형일 (숭실대학교 글로벌미디어학과)
  • Received : 2013.07.30
  • Accepted : 2013.08.19
  • Published : 2013.08.30


This paper proposes a method of tracking the hand region and detecting the fingertip using only depth images. In order to eliminate the influence of lighting conditions and obtain information quickly and stably, this paper proposes a tracking method that relies only on depth information, as well as a method of using region growing to identify errors that can occur during the tracking process and a method of detecting the fingertip that can be applied for the recognition of various gestures. First, the closest point of approach is identified through the process of transferring the center point in order to locate the tracking point, and the region is grown from that point to detect the hand region and boundary line. Next, the ratio of the invalid boundary, obtained by means of region growing, is used to calculate the validity of the tracking region and thereby judge whether the tracking is normal. If tracking is normal, the contour line is extracted from the detected hand region and the curvature and RANSAC and Convex-Hull are used to detect the fingertip. Lastly, quantitative and qualitative analyses are performed to verify the performance in various situations and prove the efficiency of the proposed algorithm for tracking and detecting the fingertip.


  1. D.H Lee and S.G Lee, "Vision-Based Finger Action Recognition by Angle Detection and Contour Analysis", ETRI Journal, vol 33, no 3, pp. 415-422, June 2011.
  2. A. Ramamoorthy, N. Vaswani, S. Chaudhury and S. Banerjee, "Recongition of dynamic hand gestures", Pattern Recognition, vol. 36, no. 9, pp. 2069-2081, September 2003.
  3. B.M. Kim, J.W. Kim, K.H. Lee, "An Application of Adaboost Learning Algorithm and Kalman Filter to Hand Detection and Tracking", The journal of KSCI, vol 10, no 4, pp. 47-56, September 2005.
  4. M. Van den Bergh, and L. Van Gool,"Combining RGB and ToF Cameras for Real-time 3D Hand Gesture Interaction", 2011 IEEE Workshop on Application of Computer Vision (WACV), pp. 66-72, January 2011.
  5. P. Trindade, J. Lobo and J. P. Barreto, "Hand gesture recognition using color and depth images enhanced with hand angular pose data", IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), pp. 71-76, September 2012.
  6. P. Suryanarayan, A. Subramanian, and D. Mandalapu, "Dynamic Hand Pose Recognition using Depth Data", In 2010 International Conference on Pattern Recognition, pp. 3105-3108, August 2010.
  7. X. Liu and K. Fujimura, "Hand gesture recognition using depth data", Proc. 6th.International Conf. on Automatic Face and Gesture Recognition, pp. 529 - 534, May 2004.
  8. M. A. Fischler, R. C. Bolles. "Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography". Comm. of the ACM, Vol 24, pp 381-395, March 1980.
  9. S.I Joo, S.H Weon, H.I Choi, "Real-time Hand Region Detection and Tracking using Depth Information", KIPS Transactions on Software and Data Engineering, vol 1, no 3, pp. 177-186, December 2012.
  10. Square Tracing Algorithm : http://www. wnloads/tutorials/contour_tracing_Abeer_George _Ghuneim/square.html