臺灣博碩士論文加值系統

人臉角度估測是一個非常重要的技術, 人臉的角度在許多方面代表了很多意義. 它可以顯現出一個人目前對環境的人事物是否感興趣,也可以代表一個人目前專注在哪個方位. 為了估測人臉所在的方位, 人臉的特徵點必須能夠準確的追蹤, 所以追蹤這些特徵點的演算法就顯得特別的重要. 粒子濾波器是一個用於追蹤的演算法,他是另一種表現卡爾曼濾波器的一種型態, 它能利用目前所觀察到的數值來預估下一個時間的狀態. 在這篇論文中我們提出了一個模型粒子濾波器來改善典型的粒子濾波器,我們利用非線性迴歸分析來訓練狀態轉移模型,來提升粒子濾波器中狀態轉移函數的效率. 而從實驗中的數據也可比較出所提出的分法比典型粒子濾波器好.

Head pose estimation is a technique that determinate the orientation of face. The orientation of human face is a important information, face is a significant symbol that show human attention and behavior. For estimating the pose of head, tracking the feature points on face is very important. Particle filter is a tracking algorithm that alternative of extend Kalman filter, it has been widely used for solving tracking problem. It predict a moving object location from observation value that contains noises. In this paper, we propose a model-based particle filter that tracks the feature point on the face and fits by AAM. the proposed model-base particle filter that use non-linear regression analysis to train a state transition model to make the state transition more efficiently. The experimental result show that model-based particle filter have better head pose estimation than classic particle filter.

Contents
ABSTRACT(in Chinese)--------------------i
ABSTRACT-------------------------------ii
Contents-------------------------------iv
List of Figures------------------------V
Chapter 1 Introduction-----------------1
Chapter 2 Related Works----------------8
2.1 Particle filter--------------------8
2.2 Active appearance model------------22
2.3 POSIT------------------------------26
Chapter 3 Proposed Method--------------29
Chapter 4 Regression Analysis----------38
Chapter 5 Experiment-------------------45
5.1 Experiment Database and datasets---45
5.1.1 Bosphorus Database---------------45
5.1.2 BU face tracking datasets--------45
5.1.3 HPEG Datasets--------------------45
5.2 Experiment Result------------------49
Chapter 6 Conclusion-------------------69
References-----------------------------71

References
[1]E. Murphy-Chutorian and M. M. Trivedi, 「Head pose estimation in computer vision: A survey,」 IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 31, no. 4, pp. 607-626, April 2009.
[2]M. Jones and P. Viola, 「Fast multi-view face detection,」 Technical report 096, mitsubishi electric research laboratories, 2003.
[3]S. Srinivasan and K. L. Boyer, 「Head pose estimation using view based eigenspaces,」 in Proc. 16th Int'l Conf. Pattern Recognition, vol. 4, pp. 302-305, 2002.
[4]A. Lanitis, C. J. Taylor, and T. F. Cootes, 「Automatic interpretation and coding of face images using flexible models,」 IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 743-756, July 1997.
[5]J. Xiao, S. Baker, I. Matthews, and T. Kanade, 「Real-time combined 2D+3D active appearance models,」 in Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. 2, pp. 535-542, 2004.
[6]T. Horprasert, Y. Yacoob, and L. S. Davis, 「Computing 3-D head orientation from a monocular image sequence,」 in Proc. 2nd Conf. Automatic Face and Gesture Recognition, pp. 242-247, October 1996.
[7]T. Maurer and C. von der Malsburg, 「Tracking and learning graphs and pose on image sequences of faces,」 in Proc. IEEE. Conf. Automatic Face and Gesture Recognition, pp. 176-181, 1996.
[8]K. Toyama, 「look, ma – no hands! hands-free cursor control with real-time 3d face tracking,」 in Proc. Conf. on Workshop Perceptual User Interfaces, pp. 49-54, 1998.
[9]D. Lowe, 「Distinctive image features from scale-invariant key points,」 Int'l J. Computer Vision, vol. 60, no. 2, pp. 91-110, 2004.
[10]S. Ohayon and E. Rivlin, 「Robust 3D head tracking using camera pose estimation,」 in Proc. IEEE Int'l. Conf. Pattern Recognition, pp. 1063-1066, 2006.
[11]R. Yang and Z. Zhang, 「Model-based head pose tracking with stereovision,」 in Proc. Int'l. Conf. Automatic Face and Gesture Recognition, pp. 242-247, 2002.
[12]A. Yilmaz, O. Javed, and M. Shah, 「Object tracking: A survey,」 ACM Computer. surveys, vol. 38, no. 4, pp. 1-45, 2006.
[13]J. Kang, I. Cohen, and G. Medioni, 「Object reacquisition using geometric invariant appearance model,」 in Proc. Int'l . Conf. on Pattern Recognition (ICPR), vol. 4, pp. 759-762, 2004.
[14]K. Sato and J. K. Aggarwal, 「Temporal spatio-velocity transform and its application to tracking and interaction,」 Computer Vision Image Understand. vol. 96, no. 2, pp. 100-128, 2004.
[15]D. Comaniciu, V. Ramesh, and P. Meer, 「Kernel-based object tracking,」 IEEE Trans Pattern Analysis and Machine Intelligence, vol. 25, no. 5, pp. 564-577, May 2003
[16]A. D. Jepson, D. J. Fleet, and T. F. El-Maraghi, 「Robust online appearance models for visual tracking,」 IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 10, pp. 1296-1311, October 2003.
[17]A. Yilmaz, O. Javed, and M. Shah, 「Object tracking: a survey,」 ACM Computer. surveys, vol. 38, no. 4, pp. 1-45, 2006.
[18]C. J. Veenman, M. J. T. Reinders, and E. Backer, 「Resolving motion correspondence for densely moving points,」 IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 23, no. 1, pp. 54-72, January 2001.
[19]Y. Chen, Y. Rui, and T. S. Huang, 「Multi-cue HMM-UKF for real-time contour tracking,」 IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 28, no. 9, pp. 1525-1529, September 2006.
[20]S. K. Zhou, R. Chellappa, and B. Moghaddam, 「Visual tracking and recognition using appearance-adaptive models in particle filters,」 IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 13, no. 11, pp. 1491-1506, November 2004.
[21]N. J. Gordon, D. J. Salmond, and A. F. M. Smith, 「Novel approach to nonlinear/non-Gaussian Bayesian state estimation,」 in Proc. Inst. Elect. Eng. F, vol. 140, pp. 107-113, 1993.
[22]R. E. Kalman, 「A new approach to linear filtering and prediction problems,」 Trans. ASME J. Basic Eng, vol. 82, pp. 34-45, March 1960.
[23]S. Kevin Zhou, R. Chellappa, and B. Moghaddam, 「Visual tracking and recognition using appearance-adaptive models in particle filters,」 IEEE Trans. Image Processing, vol. 13, no. 11, pp. 1491-1506, November 2004.
[24]M. Isard and A. Blake, 「Contour tracking by stochastic propagation of conditional density,」 in Proc. European Conf. on Computer Vision, pp. 343-356, 1996.
[25]B. North, A. Blake, M. Isard, and J. Rittscher, 「Learning and classification of complex dynamics,」 IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 9, pp. 1016-1034, September 2000.
[26]S. O. Ba and J. M. Odobez, 「A probabilistic framework for joint head tracking and pose estimation,」 in Proc. 17th Int'l Conf. on Pattern Recognition,(ICPR 2004), vol. 4, pp. 264-267, August 2004.
[27]S. O. Ba and J. M. Odobez, 「Evaluation of Multiple Cue Head Pose Estimation Algorithms in Natural Environments,」 in Proc. IEEE Int'l Conf. on Multimedia and Expo ( ICME 2005), pp. 1330-1333, July 2005.
[28]M. J. Black and D. J. Fleet, 「Probabilistic detection and tracking of motion discontinuities,」 in Proc. IEEE 7th Int'l Conf. on Computer Vision, vol. 1, pp. 551-558, 1999.
[29]S. Zhou, V. Krueger and R. Chellappa, 「Probabilistic recognition of human faces from video,「 Computer Vision Image Understanding, vol. 91, pp. 214-245, 2003.
[30]Le Lu, Xiang-Tian Dai, and G. Hager, 「A particle filter without dynamics for robust 3D face tracking,」 in Proc. Conf. on Computer Vision and Pattern Recognition Workshop, pp. 70, June 2004.
[31]J. S. Liu, R. Chen, and T. Logvinenko, 「A theoretical framework for sequential importance sampling and resampling,」 in Proc. Conf. on Sequential Monte Carlo Methods in Practice, pp. 225-246, New York, USA, January 2001.
[32]S. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, 「A tutorial on particle filters for on-line nonlinear/non-Gaussian Bayesian tracking,」 IEEE Trans. Signal Proc, vol. 50, no. 2, pp. 174-188, February 2002.
[33]P. Müller, 「Monte Carlo integration in general dynamic models,」 Contemp. Math, vol. 115, pp. 145-163, 1991.
[34]M. Isard and A. Blake, 「CONDENSATION-conditional density propagation for visual tracking,」 Int'l. J. Computer Vision, vol. 29, no. 1, August 1998.
[35]G. Qian and R. Chellappa, 「Structure from motion using sequential Monte Carlo methods,「 Int'l. J. Computer Vision, vol. 59, pp. 5-31, 2004.
[36]D. DeMenthon and L. S. Davis, 「Model-based object pose in 25 lines of code, 「 Int'l. J. Computer Vision, 1995.
[37] W. DuMouchel and F. O'Brien, 「Integrating a Robust Option into a Multiple Regression Computing Environment,」 in Proc. Conf. on Computing Science and Statistics : Proc. of the 21st Symposium on the Interface, pp. 297-301, 1989.
[38]W. Brink and M. Hoffmann, 「Real-time 3D head tracking with an AAM-based particle filter,」 in Proc. Int'l Conf. on Computer Vision Summer School, 2009.