A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
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Real-time processing in mobile devices is always a hot issue. Although face detection and stereo matching, in particular, are core elements for HRI applications, they are processes that impose the heaviest loads in real-time processing. In this article, we present novel methods of calculating disparities and face detection by using an Altair chip which can detect 32 frontal faces per frame at speed of 30 frames per second (f.p.s.). Altair can take two stereo images and process them in a frame-by-frame manner. If the left-hand image is input in the N-th time frame and then the right-hand image is input in the (N + 1)-th time frame, we can get information about left and right facial images with a one-frame delay. Then we can calculate the disparities between the faces, and can easily estimate the distance from a robot to a human with this information. In cases where several faces are detected, we classified various cases in order to identify corresponding faces. The experimental results show that we can detect faces and calculate distances in the range 0.5 m---3.5 m, with a 0.5%---8.9% error, at a processing speed of 15 f.p.s.