Detection and identification of chimpanzee faces in the wild

In this paper we present and evaluate a unified automatic image-based face detection and identification framework using two datasets of captive and free-living chimpanzee individuals gathered in uncontrolled environements. This application scenario implicates several challenging problems like deifferent lightning situations, various expressions, partial occlusion, and non-cooperative subjects. After the faces and facial feature points are detected, we use a projective transformation to align the face images. All faces are then identified using an appearence-based face recognition approach in combination with additional information from local regions of the apes´ face. We conducted open-face identification experiments for both datasets. Even though, the datasets are very challenging, the system achieved promising results and therefore has the potential to open up new ways in effective biodiversity conservation management.