Non-rigid 3D Factorization for Projective Reconstruction

In this paper we address the problem of projective reconstruction for deformable objects. Recent work in non-rigid factorization has proved that it is possible to model deformations as a linear combination of basis shapes, allowing the recovery of camera motion and 3D shape under weak perspective viewing conditions. However, the performance of these methods degrades when the object of interest is close to the camera and strong perspective distortion is present in the data. The main contribution of this work is the proposal of a practical method for the recovery of projective depths, camera motion and non-rigid 3D shape from a sequence of images under strong perspective conditions. Our approach is based on minimizing 2D reprojection errors, solving the minimization as four weighted least squares problems. Results using synthetic and real data are given to illustrate the performance of our method.

[1]  W. K. Tang,et al.  A Factorization-Based Method for Projective Reconstruction with Minimization of 2-D Reprojection Errors , 2002, DAGM-Symposium.

[2]  Mei Han,et al.  Scene Reconstruction from Multiple Uncalibrated Views , 2000 .

[3]  Takeo Kanade,et al.  Shape and motion from image streams under orthography: a factorization method , 1992, International Journal of Computer Vision.

[4]  Fumiaki Tomita,et al.  A Factorization Method for Projective and Euclidean Reconstruction from Multiple Perspective Views via Iterative Depth Estimation , 1998, ECCV.

[5]  Peter F. Sturm,et al.  A Factorization Based Algorithm for Multi-Image Projective Structure and Motion , 1996, ECCV.

[6]  Bill Triggs,et al.  Factorization methods for projective structure and motion , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[7]  Alessio Del Bue,et al.  Non-Rigid Structure from Motion using non-Parametric Tracking and Non-Linear Optimization , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.

[8]  Anders Heyden Projective Structure and Motion from Image Sequences using Subspace Methods , 1997 .

[9]  Jing Xiao,et al.  A Closed-Form Solution to Non-rigid Shape and Motion Recovery , 2004, ECCV.

[10]  Rajiv Gupta,et al.  Stereo from uncalibrated cameras , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[11]  B. Triggs Some Notes on Factorization Methods for Projective Structure and Motion Bill Triggs , 1998 .

[12]  Henning Biermann,et al.  Recovering non-rigid 3D shape from image streams , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

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

[14]  Takeo Kanade,et al.  A Paraperspective Factorization Method for Shape and Motion Recovery , 1994, ECCV.

[15]  Lorenzo Torresani,et al.  Tracking and modeling non-rigid objects with rank constraints , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.