Stable semi-local features for non-rigid shapes

Roee Litman*, Alexander M. Bronstein, Michael M. Bronstein

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Feature-based analysis is becoming a very popular approach for geometric shape analysis. Following the success of this approach in image analysis, there is a growing interest in finding analogous methods in the 3D world. Maximally stable component detection is a low computation cost and high repeatability method for feature detection in images.In this study, a diffusion-geometry based framework for stable component detection is presented, which can be used for geometric feature detection in deformable shapes. The vast majority of studies of deformable 3D shapes models them as the two-dimensional boundary of the volume of the shape. Recent works have shown that a volumetric shape model is advantageous in numerous ways as it better captures the natural behavior of non-rigid deformations. We show that our framework easily adapts to this volumetric approach, and even demonstrates superior performance. A quantitative evaluation of our methods on the SHREC’10 and SHREC’11 feature detection benchmarks as well as qualitative tests on the SCAPE dataset show its potential as a source of high-quality features. Examples demonstrating the drawbacks of surface stable components and the advantage of their volumetric counterparts are also presented.

Original languageEnglish
Title of host publicationMathematics and Visualization
EditorsMichael BreuB, Petros Maragos, Alfred Bruckstein
PublisherSpringer Heidelberg
Number of pages29
ISBN (Electronic)9783642341410
ISBN (Print)9783319912738, 9783540250326, 9783540250760, 9783540332749, 9783540886051, 9783642150135, 9783642216077, 9783642231742, 9783642273421, 9783642341403, 9783642341403, 9783642543005
StatePublished - 2013
Externally publishedYes
EventDagstuhl Workshop on Innovations for Shape Analysis: Models and Algorithms, 2011 - Dagstuhl, Germany
Duration: 3 Apr 20118 Apr 2011

Publication series

NameMathematics and Visualization
ISSN (Print)1612-3786
ISSN (Electronic)2197-666X


ConferenceDagstuhl Workshop on Innovations for Shape Analysis: Models and Algorithms, 2011


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