Introducing FoxFaces: a 3-in-1 head dataset

Amel Aissaoui (1) , Afifa Dahmane (2, 1) , Jean Martinet (1, 3, 4) , Ioan Marius Bilasco (4, 1, 3)

1 LIFL - FOX MIIRE
2 LRIA - Laboratoire de Recherche en Intelligence Artificielle [Alger]
3 Université de Lille, Sciences et Technologies
4 CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189

We introduce a new test collection named FoxFaces, dedicated to researchers in face recognition and analysis. The creation of this dataset was motivated by a lack encountered in the existing 3D/4D datasets. FoxFaces contains 3 face datasets obtained with several devices. Faces are captured with different changes in pose, expression and illumination. The presented collection is unique in two aspects: the acquisition is performed using three little constrained devices offering 2D, depth and stereo information on faces. In addition, it contains both still images and videos allowing static and dynamic face analysis. Hence, our dataset can be an interesting resource for the evaluation of 2D, 3D and bimodal algorithms on face recognition under adverse conditions as well as facial expression recognition and pose estimation algorithms in static and dynamic domains (images and videos). Stereo, color, and range images and videos of 64 adult human subjects are acquired. Acquisitions are accompanied with information about the subjects identity, gender, facial expression, approximate pose orientation and the coordinates of some manually located facial fiducial points.

Mots clés: biometric dataset; face analysis and recognition; expression; pose; multimodal

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

Amel Aissaoui, Afifa Dahmane, Jean Martinet, Ioan Marius Bilasco. Introducing FoxFaces: a 3-in-1 head dataset. International Conference on Computer Vision Theory and Applications (VISAPP), Feb 2016, Porto, Portugal. ⟨hal-01306023⟩