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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.