Multi Voxel Descriptor for 3D Texture Retrieval

  • Hero Yudo Martono Electronics Engineering Polytechnic Institute of Surabaya

Abstract

In this paper, we present a new feature descriptors  which exploit voxels for 3D textured retrieval system when models vary either by geometric shape or texture or both. First, we perform pose normalisation to modify arbitrary 3D models  in order to have same orientation. We then map the structure of 3D models into voxels. This purposes to make all the 3D models have the same dimensions. Through this voxels, we can capture information from a number of ways.  First, we build biner voxel histogram and color voxel histogram.  Second, we compute distance from centre voxel into other voxels and generate histogram. Then we also compute fourier transform in spectral space.  For capturing texture feature, we apply voxel tetra pattern. Finally, we merge all features by linear combination. For experiment, we use standard evaluation measures such as Nearest Neighbor (NN), First Tier (FT), Second Tier (ST), Average Dynamic Recall (ADR). Dataset in SHREC 2014  and its evaluation program is used to verify the proposed method. Experiment result show that the proposed method  is more accurate when compared with some methods of state-of-the-art.

Downloads

Download data is not yet available.

References

Lian, Z., Godil, A., Bustos, B., Daoudi, M., Hermans, J., Kawamura, S., ... & Ohkita, Y.. A comparison of methods for non-rigid 3D shape retrieval.Pattern Recognition, 46.1 (2013), 449-461.

Tangelder, Johan WH, and Remco C. Veltkamp. "A survey of content based 3D shape retrieval methods." Multimedia tools and applications 39.3 (2008): 441-471.

Bimbo, Alberto Del, and Pietro Pala. "Content-based retrieval of 3D models."ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) 2.1 (2006): 20-43.

Sun, Jian, Maks Ovsjanikov, and Leonidas Guibas. "A Concise and Provably Informative Multiâ€Scale Signature Based on Heat Diffusion."Computer graphics forum. Vol. 28. No. 5. Blackwell Publishing Ltd, 2009.

Reuter, Martin, et al. "Laplace–Beltrami eigenvalues and topological features of eigenfunctions for statistical shape analysis." Computer-Aided Design41.10 (2009): 739-755.

Bronstein, Alexander M., et al. "Shape google: Geometric words and expressions for invariant shape retrieval." ACM Transactions on Graphics (TOG) 30.1 (2011): 1.

Giachetti, Andrea, and Christian Lovato. "Radial symmetry detection and shape characterization with the multiscale area projection transform."Computer Graphics Forum. Vol. 31. No. 5. Blackwell Publishing Ltd, 2012.

Li, Chunyuan, and A. Ben Hamza. "Intrinsic spatial pyramid matching fordeformable 3d shape retrieval." International Journal of Multimedia Information Retrieval 2.4 (2013): 261-271.

Li, Chunyuan, and A. Ben Hamza. "A multiresolution descriptor for deformable 3D shape retrieval." The Visual Computer 29.6-8 (2013): 513-524.A

Li, Chunyuan, and A. Ben Hamza. "Spatially aggregating spectral descriptors for nonrigid 3D shape retrieval: a comparative survey." Multimedia Systems20.3 (2014): 253-281.

Cerri, Andrea, et al. "SHREC'13 track: retrieval on textured 3D models."Proceedings of the Sixth Eurographics Workshop on 3D Object Retrieval. Eurographics Association, 2013.

Biasotti, Silvia, et al. "SHREC’14 track: Retrieval and classification on textured 3D models." Proceedings of the Eurographics Workshop on 3D Object Retrieval. 2014.

Dalal, Navneet, and Bill Triggs. "Histograms of oriented gradients for human detection." Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on. Vol. 1. IEEE, 2005.

Ojala, Timo, Matti Pietikäinen, and Topi Mäenpää. "Multiresolution gray-scale and rotation invariant texture classification with local binary patterns."Pattern Analysis and Machine Intelligence, IEEE Transactions on 24.7 (2002): 971-987.

Zhao, Yang, et al. "Completed robust local binary pattern for texture classification." Neurocomputing 106 (2013): 68-76.

Chen, Jie, et al. "WLD: A robust local image descriptor." Pattern Analysis and Machine Intelligence, IEEE Transactions on 32.9 (2010): 1705-1720.

Tatsuma, Atsushi, and Masaki Aono. "Multi-Fourier spectra descriptor and augmentation with spectral clustering for 3D shape retrieval." The Visual Computer 25.8 (2009): 785-804.

Vranic, Dejan, and Dietmar Saupe. "3D shape descriptor based on 3D Fourier transform." (2001).

Murala, Subrahmanyam, R. P. Maheshwari, and R. Balasubramanian. "Local tetra patterns: a new feature descriptor for content-based image retrieval."Image Processing, IEEE Transactions on 21.5 (2012): 2874-2886.

Jacob, I. Jeena, K. G. Srinivasagan, and K. Jayapriya. "Local oppugnant color texture pattern for image retrieval system." Pattern Recognition Letters42 (2014): 72-78.

Reddy, A. Hariprasad, and N. Subhash Chandra. "Local oppugnant color space extrema patterns for content based natural and texture image retrieval." AEU-International Journal of Electronics and Communications 69.1 (2015): 290-298.

Published
2016-08-03
How to Cite
Martono, H. Y. (2016). Multi Voxel Descriptor for 3D Texture Retrieval. EMITTER International Journal of Engineering Technology, 4(1), 1-15. https://doi.org/10.24003/emitter.v4i1.110
Section
Articles