Abstract
A large number of 3D models distributed on internet has created the demand for automatic shape classification. This paper presents a novel classification method for 3D mesh shapes. Each shape is represented by the eigenvalues of an appropriately defined affinity matrix, forming a spectral embedding which achieves invariance against rigid-body transformations, uniform scaling, and shape articulation. And then, Adaboost algorithm is applied to classify the 3D models in the spectral space according to its immunity to overfitting. We evaluate the approach on the McGill 3D shape benchmark and compare the results with previous classification method, and it achieves higher classification accuracy. This method is suitable for automatic classification of 3D articulated shapes.
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.
Similar content being viewed by others
References
Liu, Z., Tang, S., Bu, S., Zhang, H.: New evaluation metrics for mesh segmentation. Computers and Graphics (SMI) 37(6), 553–564 (2013)
Liu, Z., Bu, S., Zhou, K., Gao, S., Han, J., Wu, J.: A survey on partial retrieval of 3D shapes. Journal of Computer Science and Technology 28(5), 836–851 (2013)
Barutcuoglu, Z., DeCoro, C.: Hierarchical shape classification using bayesian aggregation. In: Proceedings of IEEE Shape Modeling International (2006)
Hou, S., Lou, K., Ramani, K.: Svm-based semantic clustering and retrieval of a 3d model database. Computer Aided Design and Application 2, 155–164 (2005)
Liu, Z., Mitani, J., Fukui, Y., Nishihara, S.: A 3d shape classifier with neural network supervision. International Journal of Computer Applications in Technology 38(1-3), 134–143 (2010)
Siddiqi, K., Zhang, J., Macrini, D., Shokoufandeh, A., Bouix, S., Dickinson, S.: Retrieving articulated 3D models using medial surfaces. Machine Vision and Applications 19(4), 261–274 (2008)
Umeyama, S.: An eigen decomposition approach to weighted graph matching problem. IEEE Transactions on Pattern Analysis and Machine Intelligence 10(5), 695–703 (1988)
Scalaroff, S., Pentland, A.: Modal matching for correspondence and recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 17(6), 545–561 (1995)
Jain, V., Zhang, H.: A spectral approach to shape-based retrieval of articulated 3d models. Computer-Aided Design 39(5), 398–407 (2007)
Zhang, H., Kaick, O.V., Dyer, R.: Spectral mesh processing. Computer Graphics Forum 29(6), 1865–1894 (2010)
Fowlkes, C., Belongie, S., Chung, F., Malik, J.: Spectral grouping method using the nystrom intelligence. IEEE Transactions on Pattern Analysis and Machine Intelligence 26(2), 214–225 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Liu, Z., Zhang, F., Bu, S. (2014). Spectral Classification of 3D Articulated Shapes. In: Gurrin, C., Hopfgartner, F., Hurst, W., Johansen, H., Lee, H., O’Connor, N. (eds) MultiMedia Modeling. MMM 2014. Lecture Notes in Computer Science, vol 8326. Springer, Cham. https://doi.org/10.1007/978-3-319-04117-9_30
Download citation
DOI: https://doi.org/10.1007/978-3-319-04117-9_30
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-04116-2
Online ISBN: 978-3-319-04117-9
eBook Packages: Computer ScienceComputer Science (R0)