Shape analysis of local facial patches for 3D facial expression recognition

Ahmed Maalej (1, 2) , Boulbaba Ben Amor (1, 2) , Mohamed Daoudi (1, 2) , Anuj Srivastava (3) , Stefano Berretti (4)

1 LIFL - FOX MIIRE
2 Institut TELECOM/TELECOM Lille1
3 FSU - Florida State University [Tallahassee]
4 DSI - Dipartimento di Sistemi e Informatica

In this paper we address the problem of 3D facial expression recognition. We propose a local geometric shape analysis of facial surfaces coupled with machine learning techniques for expression classification. A computation of the length of the geodesic path between corresponding patches, using a Riemannian framework, in a shape space provides a quantitative information about their similarities. These measures are then used as inputs to several classification methods. The experimental results demonstrate the effectiveness of the proposed approach. Using Multi-boosting and Support Vector Machines (SVM) classifiers, we achieved 98.81% and 97.75% recognition average rates, respectively, for recognition of the six prototypical facial expressions on BU-3DFE database. A comparative study using the same experimental setting shows that the suggested approach outperforms previous work.

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]

Ahmed Maalej, Boulbaba Ben Amor, Mohamed Daoudi, Anuj Srivastava, Stefano Berretti. Shape analysis of local facial patches for 3D facial expression recognition. Pattern Recognition, 2011, 44 (8), pp.1581-1589. ⟨10.1016/j.patcog.2011.02.012⟩. ⟨hal-00661725⟩