In this thesis, we have investigated the problems of identity recognition and emotion detection from facial 3D shapes animations (called 4D faces). In particular, we have studied the role of facial (shapes) dynamics in revealing the human identity and their exhibited spontaneous emotion. To this end, we have adopted a comprehensive geometric framework for the purpose of analyzing 3D faces and their dynamics across time. That is, a sequence of 3D faces is first split to an indexed collection of short-term 3D sub-sequences that are represented as matrix (subspace) which define a special matrix manifold called, Grassmann manifold (set of k-dimensional linear subspaces). The geometry of the underlying space is used to effectively compare the 3D sub-sequences, compute statistical summaries (e.g. sample mean, etc.) and quantify densely the divergence between subspaces. Two different representations have been proposed to address the problems of face recognition and emotion detection. They are respectively (1) a dictionary (of subspaces) representation associated to Dictionary Learning and Sparse Coding techniques and (2) a time-parameterized curve (trajectory) representation on the underlying space associated with the Structured-Output SVM classifier for early emotion detection. Experimental evaluations conducted on publicly available BU-4DFE, BU4D-Spontaneous and Cam3D Kinect datasets illustrate the effectiveness of these representations and the algorithmic solutions for identity recognition and emotion detection proposed in this thesis. This research received the support of the Futur & Rupture program of the Mines-Telecom Institute.
Renaud Seguier, Professeur, CentraleSupélec Rennes (rapporteur), Stefanos Zafeirou, Senior Lecturer, Imperial College London (rapporteur), Bernadette Dorizzi, Professeur, Télécom SudParis (examinateur), Stefano Berretti, Associate Professor, University of Fierenze (examinateur), Hyewon Seo, CR CNRS, HDR, Université de Strasbourg (invité), Mohamed Daoudi, Professeur, Télécom Lille (directeur de thèse), Boulbaba Ben Amor, MC HDR, Télécom Lille (co-encadrant).
Thesis of the team 3D SAM defended on 02/11/2015