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Li S, Ngan KN, Paramesran R, et al. Real-Time Head Pose Tracking with Online Face Template Reconstruction. IEEE Trans Pattern Anal Mach Intell. 2015;38(9):1922-8doi: 10.1109/TPAMI.2015.2500221.
Li, S., Ngan, K. N., Paramesran, R., & Sheng, L. (2016). Real-Time Head Pose Tracking with Online Face Template Reconstruction. IEEE transactions on pattern analysis and machine intelligence, 38(9), 1922-8. https://doi.org/10.1109/TPAMI.2015.2500221
Li, Songnan, et al. "Real-Time Head Pose Tracking with Online Face Template Reconstruction." IEEE transactions on pattern analysis and machine intelligence vol. 38,9 (2016): 1922-8. doi: https://doi.org/10.1109/TPAMI.2015.2500221
Li S, Ngan KN, Paramesran R, Sheng L. Real-Time Head Pose Tracking with Online Face Template Reconstruction. IEEE Trans Pattern Anal Mach Intell. 2016 Sep;38(9):1922-8. doi: 10.1109/TPAMI.2015.2500221. Epub 2015 Nov 12. PMID: 26584487.
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IEEE Trans Pattern Anal Mach Intell. 2016 Sep;38(9):1922-8. doi: 10.1109/TPAMI.2015.2500221. Epub 2015 Nov 12.

Real-Time Head Pose Tracking with Online Face Template Reconstruction.

IEEE transactions on pattern analysis and machine intelligence

Songnan Li, King Ngi Ngan, Raveendran Paramesran, Lu Sheng

PMID: 26584487 DOI: 10.1109/TPAMI.2015.2500221

Abstract

We propose a real-time method to accurately track the human head pose in the 3-dimensional (3D) world. Using a RGB-Depth camera, a face template is reconstructed by fitting a 3D morphable face model, and the head pose is determined by registering this user-specific face template to the input depth video.

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