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 language | English |
|---|---|
| Title of host publication | 3D Imaging, Analysis and Applications |
| Pages | 185-219 |
| Number of pages | 35 |
| Volume | 9781447140634 |
| ISBN (Electronic) | 9781447140634 |
| DOIs | |
| State | Published - 1 Jun 2014 |
All Science Journal Classification (ASJC) codes
- General Computer Science