In the field of 3D head modeling and animation, feature points are often needed to mark important regions of the face and can be used to animate or deform the input model. However, an automatic detection of features remains a challenging task. This paper presents a novel approach to feature detection based on curvature and its derived descriptors, such as shape index, curvedness and Willmore energy. Four important feature regions are detected using the proposed approach - eyes, nose, mouth, ears. For each region, feature points are detected. Results show that the feature points are detected with sufficient accuracy for further use.
