Real-time multi-view facial landmark detector learned by the structured output SVM
Michal Uřičář, Vojtěch Franc, Diego Thomas, Akihiro Sugimoto, Václav Hlaváč · 2015
While the problem of facial landmark detection is getting big attention in the computer vision community recently, most of the methods deal only with near-frontal views and there is only a few really multi-view detectors available, that are capable of detection in a wide range of yaw angle (e.g. Φ ε (-90°, 90°)). We describe a multi-view facial landmark detector based on the Deformable Part Models, which treats the problem of the simultaneous landmark detection and the viewing angle estimation within a structured output classification framework. We present an easily extensible and flexible framework which provides a real-time performance on the “in the wild” images, evaluated on a challenging “Annotated Facial Landmarks in the Wild” database. We show that our detector achieves better results than the current state of the art in terms of the localization error.