A Visibility Graph based Shape Decomposition Technique
Foteini Fotopoulou, Emmanouil Z. Psarakis
2014
Abstract
In this paper, a new shape decomposition method named Visibility Shape Decomposition (VSD) is presented. Inspired from an idealization of the visibility matrix having a block diagonal form, the definition of a neighborhood based visibility graph is proposed and a two step iterative algorithm for its transformation into a block diagonal form, that can be used for a visually meaningful decomposition of the candidate shape, is presented. Although the proposed technique is applied to shapes of the MPEG7 database, it can be extended to 3D objects. The preliminary results we have obtained are promising.
References
- Biederman, I. et al. (1987). Recognition-by-components: A theory of human image understanding. Psychological review, 94(2):115-147.
- De Berg, M., Van Kreveld, M., Overmars, M., and Schwarzkopf, O. (1997). Computational geometry: algorithms and applications. Springer.
- De Goes, F., Goldenstein, S., and Velho, L. (2008). A hierarchical segmentation of articulated bodies. In Computer graphics forum, volume 27, pages 1349-1356.
- Jarvis, R. and Patrick, E. (1973). Clustering using a similarity measure based on shared nearest neighbors. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 22(11).
- Juengling, R. and Mitchell, M. (2007). Combinatorial shape decomposition. In Advances in Visual Computing, pages 183-192. Springer.
- Latecki, L. J. and Lakämper, R. (1999). Convexity rule for shape decomposition based on discrete contour evolution. Computer Vision and Image Understanding, 73(3):441-454.
- Latecki, L. J., Lakamper, R., and Eckhardt, T. (2000). Shape descriptors for non-rigid shapes with a single closed contour. In Computer Vision and Pattern Recognition, 2000. Proceedings. IEEE Conference on, volume 1, pages 424-429. IEEE.
- Lien, J.-M. and Amato, N. M. (2004). Approximate convex decomposition of polygons. pages 17-26.
- Liu, H., Liu, W., and Latecki, L. J. (2010). Convex shape decomposition. In Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on, pages 97-104. IEEE.
- Liu, Y.-S., Ramani, K., and Liu, M. (2011). Computing the inner distances of volumetric models for articulated shape description with a visibility graph. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 33(12):2538-2544.
- Mi, X. and DeCarlo, D. (2007). Separating parts from 2d shapes using relatability. In Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on, pages 1-8. IEEE.
- Ren, Z., Yuan, J., Li, C., and Liu, W. (2011). Minimum near-convex decomposition for robust shape representation. In Computer Vision (ICCV), 2011 IEEE International Conference on, pages 303-310. IEEE.
- Shapiro, L. G. and Haralick, R. M. (1979). Decomposition of two-dimensional shapes by graph-theoretic clustering. Pattern Analysis and Machine Intelligence, IEEE Transactions on, (1):10-20.
- Siddiqi, K. and Kimia, B. B. (1995). Parts of visual form: Computational aspects. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 17(3):239-251.
- Singh, M., Seyranian, G., and D.Hoffman (1999a). Parsing silhouettes: The short-cut rule. Perception and Psychophysics, 61(4):636-660.
- Singh, M., Seyranian, G. D., and Hoffman, D. D. (1999b). Parsing silhouettes: The short-cut rule. Perception & Psychophysics, 61(4):636-660.
Paper Citation
in Harvard Style
Fotopoulou F. and Z. Psarakis E. (2014). A Visibility Graph based Shape Decomposition Technique . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-003-1, pages 515-522. DOI: 10.5220/0004692005150522
in Bibtex Style
@conference{visapp14,
author={Foteini Fotopoulou and Emmanouil Z. Psarakis},
title={A Visibility Graph based Shape Decomposition Technique},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={515-522},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004692005150522},
isbn={978-989-758-003-1},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)
TI - A Visibility Graph based Shape Decomposition Technique
SN - 978-989-758-003-1
AU - Fotopoulou F.
AU - Z. Psarakis E.
PY - 2014
SP - 515
EP - 522
DO - 10.5220/0004692005150522