Abstract
With the rapid development of fast data acquisition techniques, 3D scans that record the geometric and photometric information of deformable objects are routinely acquired nowadays. To track surfaces in temporal domain or stitch partially-overlapping scans to form a complete model in spatial domain, robust and efficient feature detection for deformable shape correspondences, as an enabling method, becomes fundamentally critical with pressing needs. In this paper, we propose an efficient method to extract local features in scale spaces of both texture and geometry for deformable shape correspondences. We first build a hierarchical scale space on surface geometry based on geodesic metric, and the pyramid representation of surface geometry naturally engenders the rapid computation of scale-space features. Analogous to the SIFT, our features are found as local extrema in the scale space. We then propose a new feature descriptor for deformable surfaces, which is a gradient histogram within a local region computed by a local parameterization. Both the detector and the descriptor are invariant to isometric deformation, which makes our method a powerful tool for deformable shape correspondences. The performance of the proposed method is evaluated by feature matching on a sequence of deforming surfaces with ground truth correspondences.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Lee, C.H., Varshney, A., Jacobs, D.W.: Mesh saliency. ACM Trans. Graph. (TOG) 24, 659–666 (2005)
Wu, C., Clipp, B., Li, X., Frahm, J.M., Pollefeys, M.: 3d model matching with viewpoint-invariant patches (vip). In: CVPR (2008)
Zaharescu, A., Boyer, E., Varanasi, K., Horaud, R.: Surface feature detection and description with applications to mesh matching. In: CVPR (2009)
Zou, G., Hua, J., Dong, M., Qin, H.: Surface matching with salient keypoints in geodesic scale space. Computer Animation and Virtual Worlds 19, 399–410 (2008)
Elad, A., Kimmel, R.: On bending invariant signatures for surfaces. TPAMI 25, 1285–1295 (2003)
Novatnack, J., Nishino, K.: Scale-dependent 3d geometric features. In: ICCV (2007)
Novatnack, J., Nishino, K.: Scale-dependent/invariant local 3d shape descriptors for fully automatic registration of multiple sets of range images. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part III. LNCS, vol. 5304, pp. 440–453. Springer, Heidelberg (2008)
Hua, J., Lai, Z., Dong, M., Gu, X., Qin, H.: Geodesic distance-weighted shape vector image diffusion. TVCG 14, 1643–1650 (2008)
Reuter, M., Wolter, F.E., Peinecke, N.: Laplace-beltrami spectra as “shape-dna” of surfaces and solids. Computer-Aided Design (CAD) 38, 342–366 (2006)
Rustamov, R.: Laplace–beltrami eigenfunctions for deformation invariant shape representation. In: Symposium of Geometry Processing, SGP (2007
Lowe, D.: Distinctive image features from scale-invariant keypoints. IJCV 60, 91–110 (2004)
Mikolajczyk, K., Schmid, C.: A performance evaluation of local descriptors. TPAMI 27, 1615–1630 (2005)
Ke, Y., Sukthankar, R.: Pca-sift: A more distinctive representation for local image descriptors. In: CVPR (2004)
Tola, E., Lepetit, V., Fua, P.: A fast local descriptor for dense matching. In: CVPR (2008)
Pauly, M., Keiser, R., Gross, M.: Multi-scale feature extraction on point-sampled surfaces. Comput. Graph. Forum (CGF) 22, 281–289 (2003)
Zou, G., Hua, J., Lai, Z., Gu, X., Dong, M.: Intrinsic geometric scale space by shape diffusion. TVCG 15, 1193–1200 (2009)
Johnson, A.: Spin-images: A representation for 3-d surface matching. PhD thesis, Carnegie Mellon University (1997)
Frome, A., Huber, D., Kolluri, R., Bülow, T., Malik, J.: Recognizing objects in range data using regional point descriptors. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3023, pp. 224–237. Springer, Heidelberg (2004)
Castellani, U., Cristani, M., Fantoni, S., Murino, V.: Sparse points matching by combining 3d mesh saliency with statistical descriptors. In: Eurographics (2008)
Kimmel, R., Sethian, J.A.: Computing geodesic paths on manifolds. In: Proceedings of National Academy of Science USA (PNAS), pp. 8431–8435 (1998)
Hoppe, H.: Progressive meshes. In: SIGGRAPH, pp. 99–108 (1996)
Garland, M., Heckbert, P.S.: Surface simplification using quadric error metrics. In: SIGGRAPH, pp. 209–216 (1997)
Meyer, M., Desbrun, M., Schröder, P., Barr, A.H.: Discrete differential-geometry operators for triangulated 2-manifolds. VisMath (2002)
Meyer, T.H., Eriksson, M., Maggio, R.C.: Gradient estimation from irregularly spaced data sets. Mathematical Geology 23, 693–717 (2004)
Shapira, L., Shamir, A.: Local geodesic parametrization: An ants perspective. In: Mathematical Foundations of Scientific Visualization, Computer Graphics, and Massive Data Exploration, pp. 127–137. Springer, Heidelberg (2009)
Wang, S., Gu, X., Qin, H.: Automatic non-rigid registration of 3d dynamic data for facial expression synthesis and transfer. In: CVPR (2008)
Zhang, L., Snavely, N., Curless, B., Seitz, S.: Spacetime faces: High-resolution capture for modeling and animation. In: SIGGRAPH (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
1 Electronic Supplementary Material
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hou, T., Qin, H. (2010). Efficient Computation of Scale-Space Features for Deformable Shape Correspondences. In: Daniilidis, K., Maragos, P., Paragios, N. (eds) Computer Vision – ECCV 2010. ECCV 2010. Lecture Notes in Computer Science, vol 6313. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15558-1_28
Download citation
DOI: https://doi.org/10.1007/978-3-642-15558-1_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15557-4
Online ISBN: 978-3-642-15558-1
eBook Packages: Computer ScienceComputer Science (R0)