A direct approach for face detection on omnidirectional images
Catadioptric sensors offer abilities unexploited so far. This is especially true for face detection, and more generally, object detection. This paper presents our results of a direct approach to tackle face detection on catadioptric images. Despite no geometrical transformations, we are able to successfully apply our detector on distorted images. We expose a new method to synthesize large omnidirectional images database. Inspired from regular face detection training schemes, our method makes use of newly introduced polygonal Haar-like features. First tests demonstrated that our approach gives good performance and at the same time speeds up the detection process.