Statistical Analysis on Manifolds and Its Applications to Video Analysis

The analysis and interpretation of video data is an important component of modern vision applications such as biometrics, surveillance, motionsynthesis and web-based user interfaces. A common requirement among these very different applications is the ability to learn statistical models of appearance and motion from a collection of videos, and then use them for recognizing actions or persons in a new video. These applications in video analysis require statistical inference methods to be devised on non-Euclidean spaces or more formally on manifolds. This chapter outlines a broad survey of applications in video analysis that involve manifolds. We develop the required mathematical tools needed to perform statistical inference on manifolds and show their effectiveness in real video-understanding applications.

[1]  Antti Oulasvirta,et al.  Computer Vision – ECCV 2006 , 2006, Lecture Notes in Computer Science.

[2]  Anuj Srivastava,et al.  Bayesian and geometric subspace tracking , 2004, Advances in Applied Probability.

[3]  Roger W. Brockett Notes on Stochastic Processes on Manifolds , 1997 .

[4]  Biing-Hwang Juang,et al.  Fundamentals of speech recognition , 1993, Prentice Hall signal processing series.

[5]  Alan Edelman,et al.  The Geometry of Algorithms with Orthogonality Constraints , 1998, SIAM J. Matrix Anal. Appl..

[6]  Leon G. Higley,et al.  Forensic Entomology: An Introduction , 2009 .

[7]  F. Bookstein Size and Shape Spaces for Landmark Data in Two Dimensions , 1986 .

[8]  U. Grenander,et al.  Computational anatomy: an emerging discipline , 1998 .

[9]  R. Bhattacharya,et al.  LARGE SAMPLE THEORY OF INTRINSIC AND EXTRINSIC SAMPLE MEANS ON MANIFOLDS—II , 2003 .

[10]  M. Spivak A comprehensive introduction to differential geometry , 1979 .

[11]  Y. Chikuse Statistics on special manifolds , 2003 .

[12]  Peter Meer,et al.  Nonlinear Mean Shift over Riemannian Manifolds , 2009, International Journal of Computer Vision.

[13]  Robert E. Mahony,et al.  Optimization Algorithms on Matrix Manifolds , 2007 .

[14]  D. Kendall SHAPE MANIFOLDS, PROCRUSTEAN METRICS, AND COMPLEX PROJECTIVE SPACES , 1984 .

[15]  U. Grenander Probabilities on Algebraic Structures , 1964 .

[16]  Sudeep Sarkar,et al.  Improved gait recognition by gait dynamics normalization , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  Anuj Srivastava,et al.  On Shape of Plane Elastic Curves , 2007, International Journal of Computer Vision.

[18]  C. Small The statistical theory of shape , 1996 .

[19]  R. Brockett System Theory on Group Manifolds and Coset Spaces , 1972 .

[20]  Fatih Murat Porikli,et al.  Region Covariance: A Fast Descriptor for Detection and Classification , 2006, ECCV.

[21]  Fatih Murat Porikli,et al.  Pedestrian Detection via Classification on Riemannian Manifolds , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[22]  Anuj Srivastava,et al.  Monte Carlo extrinsic estimators of manifold-valued parameters , 2002, IEEE Trans. Signal Process..

[23]  Jianbo Shi,et al.  Detecting unusual activity in video , 2004, CVPR 2004.

[24]  Andrew Zisserman,et al.  Multiple View Geometry in Computer Vision (2nd ed) , 2003 .

[25]  Michael I. Miller,et al.  Hilbert-Schmidt Lower Bounds for Estimators on Matrix Lie Groups for ATR , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[26]  Rama Chellappa,et al.  Statistical analysis on Stiefel and Grassmann manifolds with applications in computer vision , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[27]  Anuj Srivastava,et al.  Statistical shape analysis: clustering, learning, and testing , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[28]  E. Klassen Bayesian, Geometric Subspace Tracking , 2002 .

[29]  Rama Chellappa,et al.  Identification of humans using gait , 2004, IEEE Transactions on Image Processing.

[30]  Anuj Srivastava,et al.  Analysis of planar shapes using geodesic paths on shape spaces , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[31]  H. Opower Multiple view geometry in computer vision , 2002 .

[32]  Michael I. Miller,et al.  Group Actions, Homeomorphisms, and Matching: A General Framework , 2004, International Journal of Computer Vision.

[33]  Rama Chellappa,et al.  A system identification approach for video-based face recognition , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[34]  Nicholas Ayache,et al.  Uniform Distribution, Distance and Expectation Problems for Geometric Features Processing , 1998, Journal of Mathematical Imaging and Vision.

[35]  D. Kendall,et al.  The Riemannian Structure of Euclidean Shape Spaces: A Novel Environment for Statistics , 1993 .

[36]  Andrew J. Davison,et al.  Active Matching , 2008, ECCV.

[37]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[38]  Stefano Soatto,et al.  Recognition of human gaits , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[39]  Sudeep Sarkar,et al.  The humanID gait challenge problem: data sets, performance, and analysis , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[40]  Aaron F. Bobick,et al.  Performance Analysis of Time-Distance Gait Parameters under Different Speeds , 2003, AVBPA.

[41]  Andrew Zisserman,et al.  Multiple View Geometry in Computer Vision: N-View Geometry , 2004 .

[42]  Ulf Grenander,et al.  General Pattern Theory: A Mathematical Study of Regular Structures , 1993 .

[43]  B. Moor,et al.  Subspace angles and distances between ARMA models , 2000 .

[44]  R. Bhattacharya,et al.  Nonparametic estimation of location and dispersion on Riemannian manifolds , 2002 .

[45]  H. Karcher Riemannian center of mass and mollifier smoothing , 1977 .

[46]  Rama Chellappa,et al.  Ieee Transactions on Pattern Analysis and Machine Intelligence 1 Matching Shape Sequences in Video with Applications in Human Movement Analysis. Ieee Transactions on Pattern Analysis and Machine Intelligence 2 , 2022 .

[47]  Rémi Ronfard,et al.  Free viewpoint action recognition using motion history volumes , 2006, Comput. Vis. Image Underst..

[48]  Rama Chellappa,et al.  Rate-Invariant Recognition of Humans and Their Activities , 2009, IEEE Transactions on Image Processing.

[49]  J. Ross Beveridge,et al.  Grassmann Registration Manifolds for Face Recognition , 2008, ECCV.

[50]  W. Boothby An introduction to differentiable manifolds and Riemannian geometry , 1975 .

[51]  Michael Werman,et al.  Affine Invariance Revisited , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[52]  David J. Kriegman,et al.  Illumination cones for recognition under variable lighting: faces , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[53]  Rama Chellappa,et al.  Locally time-invariant models of human activities using trajectories on the grassmannian , 2009, CVPR.

[54]  Rama Chellappa,et al.  Unsupervised view and rate invariant clustering of video sequences q , 2009 .