Skip to Main content Skip to Navigation
New interface
Conference papers

Coherent Laplacian 3-D Protrusion Segmentation

Fabio Cuzzolin 1 Diana Mateus 1 David Knossow 1 Edmond Boyer 1 Radu Horaud 1 
1 PERCEPTION - Interpretation and Modelling of Images and Videos
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology
Abstract : In this paper, an analysis of locally linear embedding (LLE) in the context of clustering is developed. As LLE conserves the local affine coordinates of points, shape protrusions as high-curvature regions of the surface are preserved. Also, LLE's covariance constraint acts as a force stretching those protrusions and making them wider separated and lower dimensional. A novel scheme for unsupervised body-part segmentation along time sequences is thus proposed in which 3-D shapes are clustered after embedding. Clusters are propagated in time, and merged or split in an unsupervised fashion to accommodate changes of the body topology. Comparisons on synthetic, and real data with ground truth, are run with direct segmentation in 3-D by EM clustering and ISOMAP-based clustering. Robustness and the effects of topology transitions are discussed.
Document type :
Conference papers
Complete list of metadata

Cited literature [24 references]  Display  Hide  Download
Contributor : Perception team Connect in order to contact the contributor
Submitted on : Tuesday, May 3, 2011 - 9:49:47 AM
Last modification on : Wednesday, May 4, 2022 - 9:56:03 AM
Long-term archiving on: : Friday, November 9, 2012 - 10:22:12 AM


Files produced by the author(s)




Fabio Cuzzolin, Diana Mateus, David Knossow, Edmond Boyer, Radu Horaud. Coherent Laplacian 3-D Protrusion Segmentation. CVPR 2008 - IEEE Conference on Computer Vision and Pattern Recognition, Jun 2008, Anchorage, United States. pp.1-8, ⟨10.1109/CVPR.2008.4587452⟩. ⟨inria-00590250⟩



Record views


Files downloads