Abstract
We present an appearance-based 3D hand posture estimation method that determines a ranked set of possible hand posture candidates from an unmarked hand image, based on an analysis by synthesis method and an image retrieval algorithm. We formulate the posture estimation problem as a nonlinear, many-to-many mapping problem in a high dimension space. A general algorithm called ISOSOM is proposed for nonlinear dimension reduction, applied to 3D hand pose reconstruction to establish the mapping relationships between the hand poses and the image features. In order to interpolate the intermediate posture values given the sparse sampling of ground-truth training data, the geometric map structure of the samples’ manifold is generated. The experimental results show that the ISOSOM algorithm performs better than traditional image retrieval algorithms for hand pose estimation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Lee, J., Kunii, T.L.: Model-Based analysis of hand posture. IEEE Computer Graphics and Applications 15, 77–86 (1995)
Rosales, R., Athitsos, V., Sclaroff, S.: 3d hand pose reconstruction using specialized mappings. In: International Conference on Computer Vision (ICCV), pp. 378–385 (2001)
Nolker, C., Ritter, H.: Visual recognition of continuous hand postures. IEEE Transactions on Neural Networks 13, 983–994 (2002)
Athitsos, V., Sclaroff, S.: An appearance-based framework for 3d hand shape classification and camera viewpoint estimation. In: Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition, Washington, DC, USA, pp. 45–50. IEEE Computer Society, Los Alamitos (2002)
Shimada, N., Kimura, K., Shirai, Y.: Real-time 3d hand posture estimation based on 2d appearance retrieval using monocular camera. In: IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems, pp. 23–30 (2001)
Wu, Y., Lin, J.Y., Huang, T.S.: Capturing natural hand articulation. In: ICCV (2001)
Zhou, H., Huang, T.S.: Tracking articulated hand motion with eigen dynamics analysis. In: Ninth IEEE International Conference on Computer Vision, pp. 1102–1109 (2003)
Kohonen, T.: Self-Organizing Maps. Springer Series in Information Sciences (2001)
Tenenbaum, J.B., Silva, V.D., Langford, J.C.: A global geometric framework for nonlinear dimensionality reduction. Science, 2319–2323 (2000)
Hu, M.K.: Visual pattern recognition by moment invariants. IRE Trans. on Information Theory, 179–187 (1962)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Guan, H., Turk, M. (2005). 3D Hand Pose Reconstruction with ISOSOM. In: Bebis, G., Boyle, R., Koracin, D., Parvin, B. (eds) Advances in Visual Computing. ISVC 2005. Lecture Notes in Computer Science, vol 3804. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11595755_77
Download citation
DOI: https://doi.org/10.1007/11595755_77
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30750-1
Online ISBN: 978-3-540-32284-9
eBook Packages: Computer ScienceComputer Science (R0)