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dc.contributor.authorLiang, Huien
dc.contributor.authorYuan, Junsongen
dc.contributor.authorThalman, Danielen
dc.identifier.citationLiang, H., Yuan, J., & Thalman, D. (2015). Egocentric hand pose estimation and distance recovery in a single RGB image. 2015 IEEE International Conference on Multimedia and Expo (ICME), 1-6.en
dc.description.abstractArticulated hand pose recovery in egocentric vision is useful for in-air interaction with the wearable devices, such as the Google glasses. Despite the progress obtained with the depth camera, this task is still challenging with ordinary RGB cameras. In this paper we demonstrate the possibility to recover both the articulated hand pose and its distance from the camera with a single RGB camera in egocentric view. We address this problem by modeling the distance as a hidden variable and use the Conditional Regression Forest to infer the pose and distance jointly. Especially, we find that the pose estimation accuracy can be further enhanced by incorporating the hand part semantics. The experimental results show that the proposed method achieves good performance on both a synthesized dataset and several real-world color image sequences that are captured in different environments. In addition, our system runs in real-time at more than 10fps.en
dc.format.extent6 p.en
dc.rights© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [].en
dc.subjectegocentric visionen
dc.subjecthand pose estimationen
dc.subjectconditional regression foresten
dc.titleEgocentric hand pose estimation and distance recovery in a single RGB imageen
dc.typeConference Paperen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen
dc.contributor.conference2015 IEEE International Conference on Multimedia and Expo (ICME)en
dc.description.versionAccepted versionen
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