Authors: Chandrashekhar N. Padole; Hugo Proença
Addresses: Department of Computer Science, IT – Instituto de Telecomunicações, University of Beira Interior, 6200-Covilhã, Portugal ' Department of Computer Science, IT – Instituto de Telecomunicações, University of Beira Interior, 6200-Covilhã, Portugal
Abstract: In the context of less constrained biometrics recognition, the use of information from the vicinity of the eyes (periocular) is considered with high potential and motivated several recent proposals. In this paper, we focus on two factors that are known to degrade the performance of periocular recognition: varying illumination conditions and subjects pose. Hence, this paper has three major purposes: 1) describe the decreases in performance due to varying illumination and subjects poses; 2) propose two techniques to improve the robustness to these factors; 3) announce the availability of an annotated dataset of periocular data (UBIPosePr), where poses vary in regular intervals, turning it especially suitable to assess the effects of misalignments between camera and subjects in periocular recognition.
Keywords: unconstrained biometrics; periocular recognition; illumination compensation; pose compensation; pose estimation; eyes; eye vicinity.
International Journal of Biometrics, 2013 Vol.5 No.3/4, pp.336 - 359
Received: 19 Jan 2013
Accepted: 08 Apr 2013
Published online: 22 Aug 2013 *