To facilitate processing of 3D objects is common to use high-level representations. The interest points are one of them. An interest point should possess a distinctive feature regarding its locality and should be stable in different instances of the object. This article proposes a descriptor based on symmetry (GISIFs) and heat diffusion (HKS). From this features, we select a set of representative points. The GISIFs referenced in this article has not been used to extract local features. We compare our results with the results of other techniques, which make up the state of the art in interest point detection. We use a benchmark that evaluates the accuracy of the selected points with respect to an ideal set of interest points.
|Title of host publication||Proceedings - 2015 41st Latin American Computing Conference, CLEI 2015|
|Editors||Alex Cuadros-Vargas, Hector Cancela, Ernesto Cuadros-Vargas|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|State||Published - 16 Dec 2015|
|Event||41st Latin American Computing Conference, CLEI 2015 - Arequipa, Peru|
Duration: 19 Oct 2015 → 23 Oct 2015
|Name||Proceedings - 2015 41st Latin American Computing Conference, CLEI 2015|
|Conference||41st Latin American Computing Conference, CLEI 2015|
|Period||19/10/15 → 23/10/15|
Bibliographical notePublisher Copyright:
© 2015 IEEE.
- geometry processing
- Heat Kernel Signature
- interest point
- Laplace-Beltrami operator