A Combined Generalized and Subject-Specific 3D Head Pose Estimation
Tan DJ, Tombari F, Navab N (2015)
Publication Type: Conference contribution
Publication year: 2015
Publisher: Institute of Electrical and Electronics Engineers Inc.
Pages Range: 500-508
Conference Proceedings Title: Proceedings - 2015 International Conference on 3D Vision, 3DV 2015
Event location: Lyon, FRA
ISBN: 9781467383325
DOI: 10.1109/3DV.2015.62
Abstract
We propose a real-time method for 3D head pose estimation from RGB-D sequences. Our algorithm relies on a Random Forest framework that is able to regress the head pose at every frame in a temporal tracking manner. Such framework is learned once from a generic dataset of 3D head models and refined online to adapt the forest to the specific characteristics of each subject. Through the qualitative experiments under different conditions, it demonstrates remarkable properties in terms of robustness to occlusions, computational efficiency and capacity of handling a variety of challenging head poses. In addition, it also outperforms the state of the art on the reference benchmark dataset with regards to the accuracy of the estimated head poses.
Involved external institutions
Germany (DE)How to cite
APA:
Tan, D.J., Tombari, F., & Navab, N. (2015). A Combined Generalized and Subject-Specific 3D Head Pose Estimation. In Michael Brown, Jana Kosecka, Christian Theobalt (Eds.), Proceedings - 2015 International Conference on 3D Vision, 3DV 2015 (pp. 500-508). Lyon, FRA: Institute of Electrical and Electronics Engineers Inc..
MLA:
Tan, David Joseph, Federico Tombari, and Nassir Navab. "A Combined Generalized and Subject-Specific 3D Head Pose Estimation." Proceedings of the 2015 International Conference on 3D Vision, 3DV 2015, Lyon, FRA Ed. Michael Brown, Jana Kosecka, Christian Theobalt, Institute of Electrical and Electronics Engineers Inc., 2015. 500-508.
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