Abstract
We present a method for estimating the distance between a camera and a human head in 2D images from a calibrated camera. Leading head pose estimation algorithms focus mainly on head orientation (yaw, pitch, and roll) and translations perpendicular to the camera principal axis. Our contribution is a system that can estimate head pose under large translations parallel to the camera’s principal axis. Our method uses a set of exemplar 3D human heads to estimate the distance between a camera and a previously unseen head. The distance is estimated by solving for the camera pose using Effective Perspective n-Point (EPnP). We present promising experimental results using the Texas 3D Face Recognition Database.
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Flores, A., Christiansen, E., Kriegman, D., Belongie, S. (2013). Camera Distance from Face Images. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2013. Lecture Notes in Computer Science, vol 8034. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41939-3_50
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DOI: https://doi.org/10.1007/978-3-642-41939-3_50
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