Results of experiment 1. ROC curves for the first experiment we conducted in this paper for the ChimpZoo dataset (A) and the ChimpTaï dataset (B). The black solid line denotes the line of equal error. We compared globally extracted Gabor features (GABOR) with pixel-based features (PIXEL). We combined the features with three different methods for feature space transformation, random projection (RAND), Principal component analysis (PCA), and locality preserving projections (LPP). For all combinations we used the SRC algorithm for classification. It can be seen that Gabor features perform best in most of the cases and are therefore better suited for describing chimpanzee faces than simple pixel-based features. Our proposed approach (GABOR + LPP), which is denoted by the solid blue line, outperforms all the other algorithms with an equal error rate (EER) of 0.1290 and 0.2938 for the ChimpZoo and ChimpTaï dataset, respectively.