A robust facial feature detection on mobile robot platform

Human face analysis on the mobile robot vision system should cope with difficult problems such as face pose variations, illumination changes, and complex backgrounds, in which problems are mainly induced from the movement of its platform. In this paper, in order to overcome such problems, an efficient facial feature detection approach based on local image region and direct pixel-intensity distributions is presented. We propose two novel concepts; the directional template for evaluating intensity distributions and the edge-like blob map image with multiple strength intensity. Using this blob map image, we show that the locations of major facial features—two eyes and a mouth—can be reliably estimated. Without the boundary information of facial area, final candidate face region is determined by both obtained locations of facial features and weighted correlations with stored facial templates.