GeoTopo: Dynamic 3D Facial Expression Retrieval Using Topological and Geometric Information
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Date
2014
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Recently, a lot of research has been dedicated to address the problem of facial expression recognition in dynamic sequences of 3D face scans. On the contrary, no research has been conducted on facial expression retrieval using dynamic 3D face scans. This paper illustrates the first results on the area of dynamic 3D facial expression retrieval. To this end, a novel descriptor is created, namely GeoTopo, capturing the topological as well as the geometric information of the 3D face scans along time. Experiments have been implemented using the angry, happy and surprise expressions of the publicly available dataset BU - 4DFE. The obtained retrieval results are very promising. Furthermore, a methodology which exploits the retrieval results, in order to achieve unsupervised dynamic 3D facial expression recognition, is presented. The aforementioned unsupervised methodology achieves classification accuracy comparable to the supervised dynamic 3D facial expression recognition state-of-the-art techniques.
Description
@inproceedings{:10.2312/3dor.20141043https::/diglib.eg.org/handle/10.2312/3dor.20141043.001-008,
booktitle = {Eurographics Workshop on 3D Object Retrieval},
editor = {Benjamin Bustos and Hedi Tabia and Jean-Philippe Vandeborre and Remco Veltkamp},
title = {{GeoTopo: Dynamic 3D Facial Expression Retrieval Using Topological and Geometric Information}},
author = {Danelakis, Antonios and Theoharis, Theoharis and Pratikakis, Ioannis},
year = {2014},
publisher = {The Eurographics Association},
ISSN = {1997-0463},
ISBN = {978-3-905674-58-3},
DOI = {/10.2312/3dor.20141043https://diglib.eg.org/handle/10.2312/3dor.20141043.001-008}
}