A Two-Layer Framework for Piecewise Linear Manifold-Based Head Pose Estimation
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Fine-grain head pose estimation from imagery is an essential operation for many human-centered systems, including pose independent face recognition and human-computer interaction (HCI) systems. It is only recently that estimation systems have evolved past coarse level classification of pose and concentrated on fine-grain estimation. In particular, the state of the art of such systems consists of nonlinear manifold embedding techniques that capture the intrinsic relationship of a pose varying face dataset. The success of these solutions can be attributed to the acknowledgment that image variation corresponding to pose change is nonlinear in nature. Yet, the algorithms are limited by the complexity of embedding functions that describe the relationship. We present a pose estimation framework that seeks to describe the global nonlinear relationship in terms of localized linear functions. A two layer system (coarse/fine) is formulated on the assumptions that coarse pose estimation can be performed adequately using supervised linear methods, and fine pose estimation can be achieved using linear regressive functions if the scope of the pose manifold is limited. A pose estimation system is implemented utilizing simple linear subspace methods and oriented Gabor and phase congruency features. The framework is tested using widely accepted pose-varying face databases (FacePix(30) and Pointing’04) and shown to perform fine head pose estimation with competitive accuracy when compared with state of the art nonlinear manifold methods.
- Balasubramanian, V. N., Ye, J., & Panchanathan, S. (2007). Biased manifold embedding: a framework for person-independent head pose estimation. In IEEE conference on computer vision and pattern recognition (pp. 1–7).
- Belhumeur, J.H., & Kriegman, D. (1997). Eigenfaces vs. fisherfaces: recognition using class-specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19, 711–720. CrossRef
- BenAbdelkader, C. (2010). Robust head pose estimation using supervised manifold learning. In ECCV’10. Proceedings of the 11th European conference on computer vision: part VI (pp. 518–531). Berlin: Springer.
- Foytik, J., Asari, V., Tompkins, R., & Youssef, M. (2010). Phase space for face pose estimation. In Advances in visual computing (pp. 49–58). CrossRef
- Fu, Y., & Huang, T. S. (2006). Graph embedded analysis for head pose estimation. In IEEE international conference on automatic face and gesture recognition (pp. 3–8).
- Gourier, N., Hall, D., & Crowley, J. L. (2004). Estimating face orientation from robust detection of salient facial features. In Proceedings of Pointing 2004, ICPR, international workshop on visual observation of deictic gestures.
- Gourier, N., Maisonnasse, J., Hall, D., & Crowley, J. L. (2006). Head pose estimation on low resolution images. In CLEAR 2006, South.
- Haj, M. A., Gonzalez, J., & Davis, L. S. (2012). On partial least squares in head pose estimation: how to simultaneously deal with misalignment. In 25th IEEE computer vision and pattern recognition.
- Kovesi, P. (1999). Image features from phase congruency. In VIDERE journal of computer vision research (Vol. 1).
- Li, Z., Fu, Y., Yuan, J., Huang, T. S., & Wu, Y. (2007). Query driven localized linear discriminant models for head pose estimation. In IEEE international conference on multimedia and expo (pp. 1810–1813).
- Little, G., Krishna, S., Black, J., & Panchanathan, S. (2005). A methodology for evaluating robustness of face recognition algorithms with respect to changes in pose and illumination angle. In IEEE international conference on acoustics, speech, and signal processing (pp. 89–92).
- Ma, B., Zhang, W., Shan, S., Chen, X., & Gao, W. (2006). Robust head pose estimation using lgbp. In International conference on pattern recognition (pp. 512–515).
- Ma, B., Shan, S., Chen, X., & Gao, W. (2008). Head yaw estimation from asymmetry of facial appearance. IEEE Transactions on Systems, Man and Cybernetics, 38, 1501–1512. CrossRef
- Melzer, T., Reiter, M., & Bischof, H. (2003). Appearance models based on kernel canonical correlation analysis. In Pattern recognition (pp. 1961–1971).
- Murphy-Chutorian, E., & Trivedi, M. M. (2008). Head pose estimation in computer vision: a survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31, 607–626. CrossRef
- Murphy-Chutorian, E., Doshi, A., & Trivedi, M. (2007). Head pose estimation for driver assistance systems: a robust algorithm and experimental evaluation. In Intelligent transportation systems conference (pp. 709–714).
- Oppenheim, A., & Lim, J. (1981). The importance of phase in signals. Proceedings of the IEEE, 69, 529–541. CrossRef
- Sherrah, J., Gong, S., & Ong, E. J. (2001). Face distributions in similarity space under varying head pose. Image and Vision Computing, 19, 807–819. CrossRef
- Stiefelhagen, R. (2004). Estimating head pose with neural networks results on the Pointing04 ICPR workshop evaluation data. In Proceedings of ICPR workshop visual observation of deictic gestures.
- Tu, J., Fu, Y., Hu, Y., & Huang, T. (2007). Evaluation of head pose estimation for studio data. In Proceedings of the 1st international evaluation conference on classification of events, activities and relationships (pp. 281–290).
- Voit, M., Nickel, K., & Stiefelhagen, R. (2006). Neural network-based head pose estimation and multi-view fusion. In LNCS. Proceedings of CLEAR workshop (pp. 299–304).
- Wang, X., Huang, X., Gao, J., & Yang, R. (2008). Illumination and person-insensitive head pose estimation using distance metric learning. In Proceedings of the 10th European conference on computer vision: part II (pp. 624–637).
- Wu, J., & Trivedi, M. M. (2005). An integrated two-stage framework for robust head pose estimation. In IEEE international workshop on analysis and modeling of faces and gestures (pp. 321–335). CrossRef
- A Two-Layer Framework for Piecewise Linear Manifold-Based Head Pose Estimation
International Journal of Computer Vision
Volume 101, Issue 2 , pp 270-287
- Cover Date
- Print ISSN
- Online ISSN
- Springer US
- Additional Links
- Head pose estimation
- Piecewise linear manifold
- Coarse to fine
- Phase congruency
- Gabor filter
- Industry Sectors