Periocular region appearance cues for biometric identification

We evaluate the utility of the periocular region appearance cues for biometric identification. Even though periocular region is considered to be a highly discriminative part of a face, its utility as an independent modality or as a soft biometric is still an open ended question. It is our goal to establish a performance metric for the periocular region features so that their potential use in conjunction with iris or face can be evaluated. In this approach, we employ the local appearance based feature representation, where the image is divided into spatially salient patches, and histograms of texture and color are computed for each patch. The images are matched by computing the distance between the corresponding feature representations using various distance metrics. We report recognition results on images captured in the visible and near-infrared (NIR) spectrum. For the color periocular region data consisting of about 410 subjects and the NIR images of 85 subjects, we obtain the Rank-1 recognition rate of 91% and 87% respectively. Furthermore, we also demonstrate that recognition performance of the periocular region images is comparable to that of face.