• KIPS Transactions on Software and Data Engineering
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• v.7 no.7
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• pp.267-274
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• 2018

This paper describes a head pose estimation method using PTZ(Pan-Tilt-Zoom) camera. When the external parameters of a camera is changed by rotation and translation, the estimated face pose for the same head also varies. In this paper, we propose a new method to estimate the head pose independently on varying the parameters of PTZ camera. The proposed method consists of 3 steps: face detection, feature extraction, and pose estimation. For each step, we respectively use MCT(Modified Census Transform) feature, the facial regression tree method, and the POSIT(Pose from Orthography and Scaling with ITeration) algorithm. The existing POSIT algorithm does not consider the rotation of a camera, but this paper improves the POSIT based on perspective projection in order to estimate the head pose robustly even when the external parameters of a camera are changed. Through experiments, we confirmed that RMSE(Root Mean Square Error) of the proposed method improve $0.6^{\circ}$ less then the conventional method.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.8
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• pp.463-471
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• 2002

In order to implement virtual endoscopy, high-speed rendering algorithm that generates accurate perspective projection images and efficient collision detection method are essential. In this paper we propose an efficient virtual endoscopy system based on volume rendering technique. It is possible to skip over empty (transparent) space using the distance value produced in preprocessing time, and it does not deteriorate image quality since it is an extension of ray-casting. It also accelerates rendering speed with minimal loss of image quality by adjusting sampling interval along a ray according to direction of the ray. Using the distance information, we can simplify the collision detection of volumetric objects.