Fast Invariant Contour-Based Classification of Hand Symbols for HCI

Video-based recognition of hand symbols is a promising technology for designing new interaction techniques for multi-user environments of the future. However, most approaches still lack performance for direct application for human-computer interaction (HCI). In this paper we propose a novel approach to contour-based recognition of hand symbols for HCI. We present adequate methods for normalization and representation of signatures extracted from boundary contours, which allow for efficient recognition of hand poses invariant to translation, rotation, scale and viewpoint variations, which are relevant for many applications in HCI. The developed classification system is evaluated on a dataset containing 13 hand symbols captured from four different persons.

[1]  Tsukasa Ogasawara,et al.  Hand pose estimation for vision-based human interface , 2001, Proceedings 10th IEEE International Workshop on Robot and Human Interactive Communication. ROMAN 2001 (Cat. No.01TH8591).

[2]  Lalit Gupta,et al.  Gesture-based interaction and communication: automated classification of hand gesture contours , 2001, IEEE Trans. Syst. Man Cybern. Syst..

[3]  Tsukasa Ogasawara,et al.  A hand-pose estimation for vision-based human interfaces , 2003, IEEE Trans. Ind. Electron..

[4]  Mircea Nicolescu,et al.  Vision-based hand pose estimation: A review , 2007, Comput. Vis. Image Underst..

[5]  Klaus Bengler,et al.  Gesture Control for Use in Automobiles , 2000, MVA.

[6]  Gerhard Rigoll,et al.  Gesture Components for Natural Interaction with In-Car Devices , 2003, Gesture Workshop.

[7]  Antonio Camurri,et al.  Gesture-Based Communication in Human-Computer Interaction , 2003, Lecture Notes in Computer Science.

[8]  Stan Sclaroff,et al.  3D hand pose reconstruction using specialized mappings , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[9]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[10]  Rogério Schmidt Feris,et al.  Multi-view Appearance-based 3D Hand Pose Estimation , 2006, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06).

[11]  Weiying Chen,et al.  Real-time 3D Hand Shape Estimation based on Image Feature Analysis and Inverse Kinematics , 2007, 14th International Conference on Image Analysis and Processing (ICIAP 2007).

[12]  Stan Sclaroff,et al.  Estimating 3D hand pose from a cluttered image , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..