Full Controllable Face Detection System Architecture for Robotic Vision

Abstract

Face detection nowadays is one of the most promising applications of image analysis and processing. One emerging application field is human-robot interaction. For many applications in this field (including face identification and expression recognition) the precision of facial feature detection and the computational burden are both critical issues. This paper presents a completely tunable hybrid method for accurate face localization based on a quick-and-dirty preliminary detection followed by a 3D refinement. Our technique guarantees complete control over the cost/quality ratio and permits to achieve the precision required for interactive applications. We use our approach to design a robotic vision architecture capable of selecting from a set of strategies to obtain the best results.