12 March 2013 Analyzing the relevance of shape descriptors in automated recognition of facial gestures in 3D images
Author Affiliations +
Abstract
The present document shows and explains the results from analyzing shape descriptors (DESIRE and Spherical Spin Image) for facial recognition of 3D images. DESIRE is a descriptor made of depth images, silhouettes and rays extended from a polygonal mesh; whereas the Spherical Spin Image (SSI) associated to a polygonal mesh point, is a 2D histogram built from neighboring points by using the position information that captures features of the local shape. The database used contains images of facial expressions which in average were recognized 88.16% using a neuronal network and 91.11% with a Bayesian classifier in the case of the first descriptor; in contrast, the second descriptor only recognizes in average 32% and 23,6% using the same mentioned classifiers respectively.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Julian S. Rodriguez A., Flavio Prieto, "Analyzing the relevance of shape descriptors in automated recognition of facial gestures in 3D images", Proc. SPIE 8650, Three-Dimensional Image Processing (3DIP) and Applications 2013, 86500L (12 March 2013); doi: 10.1117/12.2004499; https://doi.org/10.1117/12.2004499
PROCEEDINGS
12 PAGES


SHARE
Back to Top