B. H. Pawan Prasad
ABSTRACT
We present a robust head pose estimation system that is capable of estimating the 3D pose of a human head in video sequences captured using a single camera. The proposed system is able to accurately estimate the 3D pose parameters even without the knowledge of camera parameters. The face is modelled using a parametrized face mask in 3D. SIFT is used to match consecutive image frames. We propose a novel interpolation technique that captures the 3D movement of feature points to estimate the 2D-3D correspondences between the 3D model and the face image. The pose is established using the POSIT algorithm in a RANSAC framework that fits a 3D deformable face model onto the given face image. We evaluate the performance of the proposed scheme on standard test datasets. The mean absolute errors of estimated pitch, yaw and roll are found comparable and in some cases better than the results reported in literature.
- B. Ma, W. Zhang, S. Shan, X. Chen, and W. Gao, "Robust head pose estimation using LGBP," Pattern Recognition, vol. 2, pp. 512--515, 2006. Google Scholar
Digital Library
- T. Gritti, "Toward fully automated face pose estimation," in Proceedings of the International workshop on Interactive multimedia for Consumer Electronics, 2009. Google ScholarDigital Library
- E. Murphy-Chutorian and M. Trivedi, "Head pose estimation in computer vision: A survey," IEEE Transactions on PAMI, pp. 607--626, 2008. Google ScholarDigital Library
- J. Jang and T. Kanade, "Robust 3D head tracking by online feature registration," in 8th IEEE International Conference on Automatic Face and Gesture Recognition, 2008.Google Scholar
- S. Choi and D. Kim, "Robust head tracking using 3D ellipsoidal head model in particle filter," Pattern Recognition, vol. 41, no. 9, pp. 2901--2915, 2008. Google ScholarDigital Library
- S. Ohayon and E. Rivlin, "Robust 3d head tracking using camera pose estimation," in International Conference on Pattern Recognition, vol. 1, 2006. Google ScholarDigital Library
- R. Ruddarraju, A. Haro, and I. Essa, "Fast multiple camera head pose tracking," Proceedings, Vision Interface, 2003.Google Scholar
- T. Brox, B. Rosenhahn, J. Gall, and D. Cremers, "Combined region and motion-based 3D tracking of rigid and articulated objects.," IEEE Transactions on PAMI, vol. 32, no. 3, p. 402, 2010. Google ScholarDigital Library
- G. Aggarwal, A. Veeraraghavan, and R. Chellappa, "3d Facial pose tracking in Uncalibrated videos," Pattern Recognition and Machine Intelligence, pp. 515--520, 2005. Google ScholarDigital Library
- D. Lowe, "Distinctive image features from scale-invariant keypoints," International journal of computer vision, vol. 60, no. 2, pp. 91--110, 2004. Google ScholarDigital Library
- D. DeMenthon and L. Davis, "Model-based object pose in 25 lines of code," International Journal of Computer Vision, vol. 15, no. 1, pp. 123--141, 1995. Google ScholarDigital Library
- M. Fischler and R. Bolles, "Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography," Communications of the ACM, vol. 24, no. 6, pp. 381--395, 1981. Google ScholarDigital Library
- J. Ahlberg, "Candide-3-an updated parametrized face," Report No. LiTH-ISY, 2001.Google Scholar
- C. Barber, D. Dobkin, and H. Huhdanpaa, "The Quickhull algorithm for convex hulls," ACM Transactions on Mathematical Software (TOMS), vol. 22, no. 4, pp. 469--483, 1996. Google ScholarDigital Library
- M. De Berg, O. Cheong, M. Van Kreveld, and M. Overmars, Computational geometry: Algorithms and applications. Springer, 2008. Google ScholarDigital Library
- H. Edelsbrunner, Geometry and topology for mesh generation. Cambridge Univ. Press, 2001. Google ScholarDigital Library
- C. Bradley, "The Algebra of Geometry: Cartesian, Areal and Projective Co-ordinates," Highperception Ltd., Bath, 2007.Google Scholar
- F. Dornaika and J. Ahlberg, "Face and facial feature tracking using deformable models," International Journal of Image and Graphics, vol. 4, no. 3, p. 499, 2004.Google ScholarCross Ref
- F. Dornaika and J. Ahlberg, "Fitting 3D face models for tracking and active appearance model training," Image and Vision Computing, vol. 24, no. 9, pp. 1010--1024, 2006.Google ScholarCross Ref
- I. Matthews and S. Baker, "Active appearance models revisited," International Journal of Computer Vision, vol. 60, no. 2, pp. 135--164, 2004. Google ScholarDigital Library
- R. F. O. Jesorsky, K. Kirchberg, "Audio and Video based Person Authentication - AVBPA," IEEE Transactions on PAMI, 2001.Google Scholar
- R. Hartley and A. Zisserman, Multiple view geometry in computer vision. Cambridge University Press New York, NY, USA, 2003. Google ScholarDigital Library
- M. La Cascia, S. Sclaroff, and V. Athitsos, "Fast, reliable head tracking under varying illumination: an approach based on registration of texture-mapped 3 D models," IEEE Transactions on PAMI, vol. 22, no. 4, pp. 322--336, 2000. Google ScholarDigital Library
- A. Jepson, D. Fleet, and T. El-Maraghi, "Robust online appearance models for visual tracking," IEEE Transactions on PAMI, pp. 1296--1311, 2003. Google ScholarDigital Library
- J. Xiao, T. Moriyama, T. Kanade, and J. Cohn, "Robust full-motion recovery of head by dynamic templates and re-registration techniques," International Journal of Imaging Systems and Technology, vol. 13, no. 1, pp. 85--94, 2003.Google ScholarCross Ref
Index Terms
- A robust head pose estimation system for uncalibrated monocular videos
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