AN INTEGRATED APPROACH TO CONTEXTUAL FACE DETECTION
Santi Seguí, Michal Drozdzal, Petia I. Radeva, Jordi M. Vitria · 2012
face detection, object detection. Face detection is, in general, based on content-based detectors. Nevertheless, the face is a non-rigid object with well defined relations with respect to the human body parts. In this paper, we propose to take benefit of the context information in order to improve content-based face detections. We propose a novel framework for integrating multiple content- and context-based detectors in a discriminative way. Moreover, we develop an integrated scoring procedure that measures the ’faceness ’ of each hypothesis and is used to discriminate the detection results. Our approach detects a higher rate of faces while minimizing the number of false detections, giving an average increase of more than 10 % in average precision when comparing it to state-of-the art face detectors. Although face detection is a classical computer vision problem addressed from the mid nineties(Rowley et al., 1995), its application to real world problems began with the publication of the Viola & Jones algorithm