title: Efficient detection of occlusion prior to robust face recognition.
abstract: While there has been an enormous amount of research on face recognition under pose/illumination/expression changes and image degradations, problems caused by occlusions attracted relatively less attention. Facial occlusions, due, for example, to sunglasses, hat/cap, scarf, and beard, can significantly deteriorate performances of face recognition systems in uncontrolled environments such as video surveillance. The goal of this paper is to explore face recognition in the presence of partial occlusions, with emphasis on real-world scenarios (e.g., sunglasses and scarf). In this paper, we propose an efficient approach which consists of first analysing the presence of potential occlusion on a face and then conducting face recognition on the nonoccluded facial regions based on selective local Gabor binary patterns. Experiments demonstrate that the proposed method outperforms the state-of-the-art works including KLD-LGBPHS, S-LNMF, OA-LBP, and RSC. Furthermore, performances of the proposed approach are evaluated under illumination and extreme facial expression changes provide also significant results.
authors: Department of Multimedia Communications, EURECOM, 450 Route des Chappes, 06410 Biot, France.
authors: Rui
authors: 0000-0003-3784-6467
authors: R
authors: Min
authors: Center for Machine Vision Research, Department of Computer Science and Engineering, University of Oulu, P.O. Box 4500, 90014 Oulu, Finland.
authors: Abdenour
authors: 0000-0001-9092-735X
authors: A
authors: Hadid
authors: Department of Multimedia Communications, EURECOM, 450 Route des Chappes, 06410 Biot, France.
authors: Jean-Luc
authors: JL
authors: Dugelay
mesh_terms: D000465:Algorithms; D005145:Face / Q000033:anatomy & histology*; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D008297:Male; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated / Q000379:methods*