DLBP: A novel descriptor for depth image based face recognition

Amel Aissaoui (1) , Jean Martinet (2, 3) , Chabane Djeraba (1)

1 LIFL - FOX MIIRE
2 Université de Lille, Sciences et Technologies
3 CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189

Abstract: This paper presents a novel descriptor for face depth images, generalizing the well-known Local Binary Pattern (LBP), in order to enhance its discriminative power for smooth depth images. The proposed descriptor is based on detecting shape patterns from face surfaces and enables accurate and fast description of shape variation in depth images. It is in the same form as conventional LBP, so patterns can be readily combined to form joint histograms to represent depth faces. The descriptor is computationally very simple, rapid and it is totally training-free. When we associate our descriptor in a face recognition scheme based on nearest neighbor classifier, it shows its discriminative power in depth based face recognition comparing to the conventional LBP and other extensions proposed for 3D face recognition. Many experiments are conducted on different databases in order to evaluate our method.

Mots clés: Face recognition; Depth images; Local Binary Pattern (LBP)

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

Amel Aissaoui, Jean Martinet, Chabane Djeraba. DLBP: A novel descriptor for depth image based face recognition. IEEE International Conference on Image Processing, Oct 2014, Paris, France. pp.298-302, ⟨10.1109/ICIP.2014.7025059⟩. ⟨hal-01532719⟩