Minimizing Illumination Differences for 3D to 2D Face Recognition Using Lighting Maps
作者： Xi Zhao , Georgios Evangelopoulos , Dat Chu , Shishir Shah , Ioannis A. Kakadiaris
DOI: 10.1109/TCYB.2013.2291196
关键词:
摘要: Asymmetric 3D to 2D face recognition has gained attention from the research community since real-world application of is limited by unavailability inexpensive data acquisition equipment. A system explicitly relies on facial account for uncontrolled image conditions related head pose or illumination. We build upon such a system, which matches relit gallery textures with pose-normalized probe images, using meshes. The relighting process, however, based an assumption indoor lighting and limits performance outdoor images. In this paper, we propose novel method minimizing illumination difference unlighting texture via albedo estimation maps. algorithm evaluated challenging databases (UHDB30, UHDB11, FRGC v2.0) drastic variations. experimental results demonstrate robustness our estimating both captured effectiveness efficiency normalization in recognition.
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