Recovering Articulated Non-rigid Shapes, Motions and Kinematic Chains from Video

1. Zhou, H., Huang, T.: Recovering Articulated Motion with a Hierarchical Factorization Method. In: Gesture Workshop 2003, pp. 140–151 (2003)

   Google Scholar 

2. Taylor, C.J.: Reconstruction of Articulated Objects from Point Correspondences in a Single Image. In: CVPR, p. 677 (2000)

   Google Scholar 

3. Bregler, C., Malik, J.: Tracking people with twists and exponential maps. In: CVPR, pp. 8–15 (1998)

   Google Scholar 

4. Hogg, D.: Model-based vision: A program to see a walking person. Image and Vision Computing 1(1), 5–20 (1983)

   Article  Google Scholar 

5. Sminchisescu, C., Triggs, B.: Covariance Scaled Sampling for Monocular 3D Body Tracking. In: Proc. CVPR, vol. I, pp. 447–454 (2001)

   Google Scholar 

6. Fischler, M.A., Bolles, R.C.: Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. Comm. of the ACM 24, 381–395 (1981)

   Article  MathSciNet  Google Scholar 

7. Costeira, J.P., Kanade, T.: A Multibody Factorization Method for Independently Moving Objects. IJCV 29(3), 159–179 (1998)

   Article  Google Scholar 

8. Bregler, C., Hertzmann, A., Biermann, H.: Recovering Non-Rigid 3D Shape from Image Streams. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2000) (June 2000)

   Google Scholar 

9. Brand, M.: Morphable 3D models from video. In: CVPR, vol. II, pp. 456–463 (2001)

   Google Scholar 

10. Xiao, J., Chai, J.-x., Kanade, T.: A closed-form solution to non-rigid shape and motion recovery. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3024, pp. 573–587. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

11. Ichimura, N.: Motion segmentation based on factorization method and discriminant criterion. In: Proc. IEEE Int. Conf. Computer Vision, pp. 600–605 (1999)

    Google Scholar 

12. Kanatani, K.: Motion segmentation by subspace separation and model selection:model selection and reliability evaluation. Intl. J. of Image and Graphics 2(2), 179–197 (2002)

    Article  Google Scholar 

13. Weiss, Y.: Segmentation using eigenvectors: A unifying view. In: International Conference on Computer Vision, Corfu, Greece, September 1999, pp. 975–982 (1999)

    Google Scholar 

14. Ng, A., Jordan, M., Weiss, Y.: On spectral clustering: analysis and an algorithm. In: Advances in Neural Information Processing Systems 14, MIT Press, Cambridge (2002)

    Google Scholar 

15. Shi, J., Malik, J.: Normalized Cuts and Image Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) (2000)

    Google Scholar 

16. Tomasi, C., Kanade, T.: Shape and motion from image streams under orthography: a factorization method. IJCV 9(2), 137–154 (1992)

    Article  Google Scholar 

17. Vidal, R., Hartley, R.: Motion Segmentation with Missing Data using PowerFactorization and GPCA. In: IEEE Conference on Computer Vision and Pattern Recognition (2004)

    Google Scholar 

18. Vidal, R., Ma, Y., Sastry, S.: Generalized Principal Component Analysis (GPCA). In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2003) (June 2003)

    Google Scholar 

19. Vidal, R., Ma, Y., Piazzi, J.: A New GPCA Algorithm for Clustering Subspaces by Fitting, Differentiating and Dividing Polynomials. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2004), June 27-July 02 (2004)

    Google Scholar 

20. Yan, J., Pollefeys, M.: A Factorization-based Approach to Articulated Motion Recovery. In: IEEE Conf. on Computer Vision and Pattern Recognition (2005)

    Google Scholar 

21. Yan, J., Pollefeys, M.: A general framework for motion segmentation: Independent, articulated, rigid, non-rigid, degenerate and non-degenerate. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3954, pp. 94–106. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

22. Tresadern, P., Reid, I.: Articulated Structure From Motion by Factorization. In: Proc. IEEE Conf on Computer Vision and Pattern Recognition (2005)

    Google Scholar 

23. Golub, G., van Loan, A.: Matrix Computations. Johns Hopkins U. Press (1996)

    Google Scholar 

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