• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.7
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• pp.532-538
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• 2013

This paper describes a vision-based only attitude estimation technique for the leader in the formation flight. The feature points in image obtained from the X-PLANE simulator are extracted by the SURF(Speed Up Robust Features) algorithm. We use POSIT(Pose from Orthography and Scaling with Iteration) algorithm to estimate attitude. Finally we verify that attitude estimation using vision only can yield small estimated error of $1.1{\sim}1.76^{\circ}$.

• 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.