Analyzing the relevance of shape descriptors in automated recognition of facial gestures in 3D images

Julian S. Rodriguez A.; Flavio Prieto

doi:10.1117/12.2004499

12 March 2013 Analyzing the relevance of shape descriptors in automated recognition of facial gestures in 3D images

Julian S. Rodriguez A., Flavio Prieto

Proceedings Volume 8650, Three-Dimensional Image Processing (3DIP) and Applications 2013; 86500L (2013) https://doi.org/10.1117/12.2004499
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States

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.

Citation Download Citation

Julian S. Rodriguez A. and 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); https://doi.org/10.1117/12.2004499

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