@inbook{18325,
  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.},
  author       = {Bronstein, Alexander and Bronstein, Michael M. and Ovsjanikov, Maks},
  booktitle    = {3D Imaging, Analysis and Applications},
  editor       = {Pears, Nick and Liu, Yonghuai and Bunting, Peter},
  isbn         = {9781447140627},
  pages        = {185--219},
  publisher    = {Springer Nature},
  title        = {{Feature-Based Methods in 3D Shape Analysis}},
  doi          = {10.1007/978-1-4471-4063-4_5},
  year         = {2012},
}