3D Shape Retrieval using Uncertain Semantic Query - A Preliminary Study
Hattoibe Aboubacar, Vincent Barra, Gaëlle Loosli
2014
Abstract
The recent technological progress contributes to a huge increase of 3D models available in digital forms. Numerous applications were developed to deal with this amount of information, especially for 3D shape retrieval. One of the main issues is to break the semantic gap between shapes desired by users and shapes returned by retrieval methods. In this paper, we propose an algorithm to address this issue. First the user gives a semantic request. Second, a fuzzy 3D-shape generator sketches out suitable 3D-shapes. Those shapes are filtered by the user or a learning machine to select the ones that match the semantic query. Then, we use a state-of-the-art retrieval method to return real-world 3D shapes that match this semantic query. This algorithm is used to retrieve object in SHREC’07 database. The results are good and promising.
References
- Bach, F., Lanckriet, G. R. G., and Jordan, M. I. (2004). Multiple kernel learning, conic duality, and the smo algorithm. In Proceedings of the twenty-first international conference on Machine learning, ICML 7804, New York, NY, USA. ACM.
- Barra, V. and Biasotti, S. (2013). 3d shape retrieval using kernels on extended reeb graphs. Pattern Recognition.
- Biasotti, S., Floriani, L. D., Falcidieno, B., Frosini, P., Giorgi, D., Landi, C., L.Papaleo, and Spagnuolo, M. (2008). Describing shapes by geometrical-topological properties of real functions. Computing Surveys, 40(4). In: Computing Surveys, vol. 40 (4) ACM, 2008.
- Chaudhuri, S., Kalogerakis, E., Guibas, L., and Koltun, V. (2011). Probabilistic reasoning for assembly-based 3d modeling. ACM Transactions on Graphics (Proc. SIGGRAPH), 30(4).
- Eitz, M., Hays, J., and Alexa, M. (2012). How do humans sketch objects? ACM Transactions on Graphics (Proceedings SIGGRAPH), 31(4):44:1-44:10.
- Funkhouser, T., Kazhdan, M., Shilane, P., Min, P., Kiefer, W., Tal, A., Rusinkiewicz, S., and Dobkin, D. (2004). Modeling by example. ACM Transactions on Graphics (Proc. SIGGRAPH).
- Giorgi, D., Biasotti, S., and Paraboschi, L. (2007). Watertight models track. Research report, IMATI, Genova, Italy.
- Giorgi, D., Frosini, P., Spagnuolo, M., and Falcidieno, B. (2010). 3d relevance feedback via multilevel relevance judgements. Vis. Comput., 26(10):1321-1338.
- Han, D., W., and Li, Z. (2008). Semantic image classification using statistical local spatial relations model. Multimedia Tools and Applications, 39(2):169-188.
- Kalogerakis, E., Chaudhuri, S., Koller, D., and Koltun, V. (2012). A probabilistic model of component-based shape synthesis. ACM Transactions on Graphics, 31(4).
- Khan, S. S. and Madden, M. G. (2009). A survey of recent trends in one class classification. In Artificial Intelligence and Cognitive Science, pages 181-190.
- Lanckriet, G. R. G., Cristianini, N., Bartlett, P., Ghaoui, L. E., and Jordan, M. I. (2004). Learning the kernel matrix with semidefinite programming. Journal of Machine Learning Research, 5:27-72.
- Rakotomamonjy, A., Bach, F., Canu, S., and Grandvalet, Y. (2008). Simplemkl. Journal of Machine Learning Research.
- Schlkopf, B. and Smola, A. J. (2001). Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. MIT Press, Cambridge, MA, USA.
- Sonnenburg, S., Rtsch, G., Schfer, C., and Schlkopf, B. (2006). Large scale multiple kernel learning. Journal of Machine Learning Research, 7:1531-1565.
- Tangelder, J. W. H. and Veltkamp, R. C. (2008). A survey of content based 3d shape retrieval methods. Multimedia Tools and Applications, 39(3):441-471.
- Tax, D. M. J. and Duin, R. P. W. (2004). Support vector data description. Machine Learning, 54(1):45-66.
- Zhang, Z. and Jin, J. (2010). Fuzzy relevance feedback in content-based 3d model retrieval. In Proceedings of the seventh international conference on Fuzzy Systems and Knowledge Discovery, pages 565-568.
Paper Citation
in Harvard Style
Aboubacar H., Barra V. and Loosli G. (2014). 3D Shape Retrieval using Uncertain Semantic Query - A Preliminary Study . In Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-018-5, pages 600-607. DOI: 10.5220/0004819106000607
in Bibtex Style
@conference{icpram14,
author={Hattoibe Aboubacar and Vincent Barra and Gaëlle Loosli},
title={3D Shape Retrieval using Uncertain Semantic Query - A Preliminary Study},
booktitle={Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2014},
pages={600-607},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004819106000607},
isbn={978-989-758-018-5},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - 3D Shape Retrieval using Uncertain Semantic Query - A Preliminary Study
SN - 978-989-758-018-5
AU - Aboubacar H.
AU - Barra V.
AU - Loosli G.
PY - 2014
SP - 600
EP - 607
DO - 10.5220/0004819106000607