Multi-scale, multi-feature vector flow active contours for automatic multiple-face detection

To automatically detect faces in real-world images presenting challenges such as complex background and multiple foregrounds, we propose a new method which is based on parametric active contours and which does not require any supervision, model nor training. The proposed face detection technique computes multi-scale representations of an input color image and based on them initializes the multi-feature vector flow active contours which, after their evolution, automatically delineate the faces. In this way, our computationally efficient system successfully detects faces in complex pictures with varying numbers of persons of diverse gender and origins and with different types of face views (front/profile) and variate face alignments straight/oblique), as demonstrated in tests carried out on several datasets.