Shape Analysis of Elastic Curves in Euclidean Spaces

This paper introduces a square-root velocity (SRV) representation for analyzing shapes of curves in euclidean spaces under an elastic metric. In this SRV representation, the elastic metric simplifies to the IL2 metric, the reparameterization group acts by isometries, and the space of unit length curves becomes the unit sphere. The shape space of closed curves is the quotient space of (a submanifold of) the unit sphere, modulo rotation, and reparameterization groups, and we find geodesics in that space using a path straightening approach. These geodesics and geodesic distances provide a framework for optimally matching, deforming, and comparing shapes. These ideas are demonstrated using: 1) shape analysis of cylindrical helices for studying protein structure, 2) shape analysis of facial curves for recognizing faces, 3) a wrapped probability distribution for capturing shapes of planar closed curves, and 4) parallel transport of deformations for predicting shapes from novel poses.

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

[2]  Wei Liu,et al.  Protein structure alignment using elastic shape analysis , 2010, BCB '10.

[3]  Anuj Srivastava,et al.  On Analyzing Symmetry of Objects using Elastic Deformations , 2009, VISAPP.

[4]  Pietro Perona,et al.  One-shot learning of object categories , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Anuj Srivastava,et al.  Looking for Shapes in Two-Dimensional Cluttered Point Clouds , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  J. Milnor Topology from the differentiable viewpoint , 1965 .

[7]  Hassen Drira,et al.  A Riemannian analysis of 3D nose shapes for partial human biometrics , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[8]  Laurent Younes,et al.  Computable Elastic Distances Between Shapes , 1998, SIAM J. Appl. Math..

[9]  J. Shah An H 2 type Riemannian metric on the space of planar curves ∗ , 2006 .

[10]  Ronen Basri,et al.  Curve Matching Using the Fast Marching Method , 2003, EMMCVPR.

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

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

[13]  Alexander M. Bronstein,et al.  Three-Dimensional Face Recognition , 2005, International Journal of Computer Vision.

[14]  Anuj Srivastava,et al.  Elastic Shape Models for Face Analysis Using Curvilinear Coordinates , 2009, Journal of Mathematical Imaging and Vision.

[15]  Philip N. Klein,et al.  On Aligning Curves , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Michael I. Miller,et al.  Dynamic Programming Generation of Curves on Brain Surfaces , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[17]  Michael I. Miller,et al.  Transport of Relational Structures in Groups of Diffeomorphisms , 2008, Journal of Mathematical Imaging and Vision.

[18]  Anuj Srivastava,et al.  The Labeling of Cortical Sulci using Multidimensional Scaling , 2008, The MIDAS Journal.

[19]  M. Kilian,et al.  Geometric modeling in shape space , 2007, SIGGRAPH 2007.

[20]  Anuj Srivastava,et al.  A Novel Representation for Riemannian Analysis of Elastic Curves in Rn , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[21]  Anuj Srivastava,et al.  Joint Gait-Cadence Analysis for Human Identification Using an Elastic Shape Framework , 2010 .

[22]  Daniel Cremers,et al.  Shape Matching by Variational Computation of Geodesics on a Manifold , 2006, DAGM-Symposium.

[23]  R. Palais Morse theory on Hilbert manifolds , 1963 .

[24]  Anuj Srivastava,et al.  Removing Shape-Preserving Transformations in Square-Root Elastic (SRE) Framework for Shape Analysis of Curves , 2007, EMMCVPR.

[25]  Silvio Savarese,et al.  View Synthesis for Recognizing Unseen Poses of Object Classes , 2008, ECCV.

[26]  J. C. Gore,et al.  Comparison of Group Average and Individual Differences in Brain Morphometry in Williams Syndrome , 2008 .

[27]  Michael G. Strintzis,et al.  3-D Face Recognition With the Geodesic Polar Representation , 2007, IEEE Transactions on Information Forensics and Security.

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

[29]  D. Mumford,et al.  Riemannian Geometries on Spaces of Plane Curves , 2003, math/0312384.

[30]  Anuj Srivastava,et al.  Riemannian Analysis of Probability Density Functions with Applications in Vision , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[31]  Stefano Soatto,et al.  A New Geometric Metric in the Space of Curves, and Applications to Tracking Deforming Objects by Prediction and Filtering , 2011, SIAM J. Imaging Sci..

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

[33]  Anuj Srivastava,et al.  Three-Dimensional Face Recognition Using Shapes of Facial Curves , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

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

[35]  Andrea C. G. Mennucci,et al.  Metrics of Curves in Shape Optimization and Analysis , 2013 .

[36]  D. Mumford,et al.  A Metric on Shape Space with Explicit Geodesics , 2007, 0706.4299.

[37]  N. Čencov Statistical Decision Rules and Optimal Inference , 2000 .

[38]  L. Younes,et al.  Statistics on diffeomorphisms via tangent space representations , 2004, NeuroImage.