Feature Extraction Based on Hybrid Skeleton for Human-Robot Interaction

휴먼-로봇 인터액션을 위한 하이브리드 스켈레톤 특징점 추출

  • 주영훈 (군산대학교 전자정보공학부) ;
  • 소제윤 (군산대학교 전자정보공학부)
  • Published : 2008.02.01


Human motion analysis is researched as a new method for human-robot interaction (HRI) because it concerns with the key techniques of HRI such as motion tracking and pose recognition. To analysis human motion, extracting features of human body from sequential images plays an important role. After finding the silhouette of human body from the sequential images obtained by CCD color camera, the skeleton model is frequently used in order to represent the human motion. In this paper, using the silhouette of human body, we propose the feature extraction method based on hybrid skeleton for detecting human motion. Finally, we show the effectiveness and feasibility of the proposed method through some experiments.


  1. D. M. Gavrila and L. S. Davis, 'Towards 3D model based tracking and recognition of human movement: a multi view approach,' Int Workshop on Face and Gesture Recognition, vol. 162479, pp. 272-277, 1995
  2. V. I. Pavlovic, R. Sharma, and T. S. Huang, 'Visual interpretation of hand gestures for human computer interaction: A review,' IEEE, Transaction on PAMI, vol. 19, no. 7, pp. 677, July, 1997
  3. G. V. Veres, L. Gordon, J. N. Carter, and M. S. Nixon. 'What image information is important in silhouette based gait recognition?,' 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. vol. 2, pp. 776-782, 2004
  4. C. R. Wren, A. Azarbayejani, T. Darrell, and A. Pentland, 'Pfinder: real-time tracking of the human body,' IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 780-785, 1997
  5. I. Haritaoglu, D. Harwood, and L. S. Davis, 'W4: Real-time surveillance of people and their activities,' IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 22, no. 8, pp. 809-830, 2000
  6. R. Cutler and L. Davis, 'Robust real-time periodic motion detection, analysis, and applications,' IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 22, no. 8, pp. 781-796, 2000
  7. H. F. and A. J. Lipton, 'Real time human motion analysis by image skeletonization,' Proceedings of The 4th Workshop of Applications of Computer Vision, pp. 15-21, 1998
  8. Y. Li, A. Hilton, and J. Illingworth, 'A relaxation algorithm for real-time multiple view 3D-tracking,' Journal of Image and Vision Computing, vol. 20, pp. 841-859, 2002
  9. R. Hoshino, S. Yonemoto, D. Arita, and R. Taniguchi. 'Real time motion capture system based-on silhouette contour analysis and inverse kinematics,' 7th Korea- Japan Joint Workshop on Computer Vision, vol. 7, pp. 157-163, 2001
  11. Bruce D. Lucas and T. Kanade. 'An iterative image registration technique with an application to stereo vision,' International Joint Conference on Artificial Intelligence, pp. 674-679, 1981
  12. C. Xu, and J. Prince, 'Snakes, shapes, and gradient vector flow,' IEEE. Transactions on Image Processing, vol. 7, no. 3, pp. 359-369, 1998