Feature-based methods in 3D shape analysis

Alexander M. Bronstein, Michael M. Bronstein, Maks Ovsjanikov

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

The computer vision and pattern recognition communities have recently witnessed a surge in feature-based methods for numerous applications including object recognition and image retrieval. Similar concepts and analogous approaches are penetrating the world of 3D shape analysis in a variety of areas including non-rigid shape retrieval and matching. In this chapter, we present both mature concepts and the state-of-the-art of feature-based approaches in 3D shape analysis. In particular, approaches to the detection of interest points and the generation of local shape descriptors are discussed. A wide range of methods is covered including those based on curvature, those based on difference-of-Gaussian scale space, and those that employ recent advances in heat kernel methods.

Original languageEnglish
Title of host publication3D Imaging, Analysis and Applications
Pages185-219
Number of pages35
Volume9781447140634
ISBN (Electronic)9781447140634
DOIs
StatePublished - 1 Jun 2014

All Science Journal Classification (ASJC) codes

  • General Computer Science

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