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Head pose estimation in thermal images for human and robot interaction

Xinguo Yu, Weiwen Kevin Chua, Dong Li, Kah Eng Hoe, Liyuan Li

Year
2010
Citations
10

Abstract

Head pose estimation is one of key steps for human and robot interaction because head pose is highly related with the attention of human to robot. Although head pose estimation has progressed in the past few decades, existing algorithms for visual imagery are not fast enough for smooth human and robot interaction. This paper proposes an algorithm to estimate head pose of a previously unseen head from thermal images, motivated by the fact that thermal imagery provides us the possibility to develop light-weight computing algorithm for estimating head pose. The proposed algorithm has multiple merits. Firstly, it is a fully-automatic algorithm. That does not require any manual initialization. Second, its operation is very simple. It recognizes the head pose from a single image. Third, it is a light-weight computing algorithm. This is mainly because it has a fast head localization procedure. The proposed algorithm can estimate head pose at 110 fps. Last, it is a very robust algorithm in head localization. The performance in head pose estimation is promising.

Keywords

InitializationPoseArtificial intelligenceHead (geology)Computer visionComputer scienceRobotHuman headArticulated body pose estimation3D pose estimation

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