Driver´s Head Pose Measurement and Corner Center Detection

In this paper, we describe development of driver´s head pose measurement and cornea center detection system. Similar researches have been performed so far. Most researches are based on feature point detection by the template matching. In general, the template matching has the weakness to the change in the expansion and contraction, rotation and brightness. To overcome these faults, three-dimensional shape alignment is introduced. Three-dimensional shape alignment is performed between driver´s face model and shape data obtained in each time. Then, three-dimensional shapes are analyzed by stereovision. Moreover, shape alignment is performed by ICP registration. ICP registration can achieve high accuracy alignment, but needs huge computational effort, in general. To solve this problem, this paper introduces a reduction in volume of data based on pattern information in the image, coarse-to-fine search, and SIMD computing. Furthermore, this paper describes the cornea center estimation technique. At first, this technique extracts the eye region image from result of the head pose measurement. Afterward, the cornea center is estimated by recognition of eye contour and the ellipse fitting of cornea. It was confirmed by experiments that the proposed technique can measure in high accuracy, and the proposed technique is available in real environment