title: Intrinsic illumination subspace for lighting insensitive face recognition.
abstract: We introduce the intrinsic illumination subspace and its application for lighting insensitive face recognition in this paper. The intrinsic illumination subspace is constructed from illumination images of intrinsic images, which is a midlevel description of appearance images and can be useful for many visual inferences. This subspace forms a convex polyhedral cone and can be efficiently represented by a low-dimensional linear subspace, which enables an analytic generation of illumination images under varying lighting conditions. When only objects of the same class, such as faces, are concerned, a class-based generic intrinsic illumination subspace can be constructed in advance and used for novel objects of the same class. Based on this class-based generic subspace, we propose a lighting normalization method for lighting insensitive face recognition, where only a single input image is required. The generic subspace is used as a bootstrap subspace for illumination images of novel objects. Face recognition experiments are performed to demonstrate the effectiveness of the proposed lighting normalization method and verify empirically that the class-based generic subspace is applicable to novel objects. Our method is simple and fast, which makes it useful for real-time applications, embedded systems, or mobile devices with limited resources.
authors.affiliation: Institute of Information Science, Academia Sinica, Taipei 115, Taiwan. cpchen@iis.sinica.edu.tw
authors.forename: Chia-Ping
authors.initials: CP
authors.lastname: Chen
authors.forename: Chu-Song
authors.initials: CS
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D056667:Biometric Identification / Q000379:methods*; D016208:Databases, Factual; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008029:Lighting; D025341:Principal Component Analysis