Landmark detection from 3D mesh facial models for image-based analysis of dysmorphology

Marwa Chendeb, Claudio Tortorici, Hassan Almuhairi, Habiba Alsafar, Marius Linguraru, Naoufel Werghi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Facial landmark detection is a task of interest for facial dysmorphology, an important factor in the diagnosis of genetic conditions. In this paper, we propose a framework for feature points detection from 3D face images. The method is based on 3D Constrained Local Model (CLM) which learns both global variations in the 3D facial scan and local changes around every vertex landmark. Compared to state of the art methods our framework is distinguished by the following novel aspects: 1) It operates on facial surfaces, 2) It allows fusion of shape and color information on the mesh surface, 3) It introduces the use of LBP descriptors on the mesh. We showcase our landmarks detection framework on a set of scans including down syndrome and control cases. We also validate our method through a series of quantitative experiments conducted with the publicly available Bosphorus database.

Original languageBritish English
Title of host publication2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages169-172
Number of pages4
ISBN (Electronic)9781424492718
DOIs
StatePublished - 4 Nov 2015
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
Duration: 25 Aug 201529 Aug 2015

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2015-November
ISSN (Print)1557-170X

Conference

Conference37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
Country/TerritoryItaly
CityMilan
Period25/08/1529/08/15

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