Occlusion Detection for Face Image Quality Assessment

The accuracy of 2D-image-based face recognition systems depends on the quality of the compared face images. One factor that affects the recognition accuracy is the occlusion of face regions, e.g., by opaque sunglasses or medical face masks. Being able to assess the quality of captured face images can be useful in various scenarios, e.g., in a border entry/exit system. This paper discusses a method for detecting face occlusions and for measuring the percentage of occlusion of a face using face segmentation and face landmark estimation techniques. The method is applicable to arbitrary face images, not only to frontal or nearly frontal face images. The method was evaluated by applying it to publicly available face image data sets and analyzing the results obtained. The evaluation shows that the proposed method enables the effective detection of face occlusions.