3D motion segmentation from straight-line optical flow

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4577 LNCS, Issue , 2007, Pages 85-94

  Zhang, Jing ^a   Shi, Fanhuai ^a   Wang, Jianhua ^a   Liu, Yuncai ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

OPTICAL FLOWS; POLYNOMIAL APPROXIMATION;

MOTION MODELS; MULTIBODY LINE OPTICAL FLOW CONSTRAINT(MLOFC); POLYNOMIAL EQUATIONS;

IMAGE SEGMENTATION;

EID: 37249014392     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-73417-8_15     Document Type: Conference Paper

References (17)

1. Rittscher, J., Tu, P.H., Krahnstoever, N.: Simultaneous estimation of segmentation and shape. In: IEEE Conference on Computr Vision and Pattern Recognition (2005)
2. Torr, P.H.S.: Geometric motion segmentation and model selection Phil. Trans. Royal Society of London A (1998)
3. Feng, X., Perona, P.: Scene segmentation from 3d motion (1998)
4. Torr, P., Szeliski, R., Anandan, P.: An integrated bayesian approach to layer extraction from image sequences. IEEE Trans. on Pattern Analysis and Machine Intelligence 23, 297-303 (2001)
5. Vidal, R., Ma, Y., Sastry, S.: Generalized principal component analysis (gpca). In: IEEE Conference on Computr Vision and Pattern Recognition, pp. 621-628 (2003)
6. Vidal, R., Ma, Y.: A unified algebraic approach to 2-d and 3-d motion segmentation. In: European Conference on Computer Vision, pp. 1-15 (2004)
7. Singaraju, D., Vidal, R.: A bottom up algebraic approach to motion segmentation. In: Asian Conference on Computer Vision, pp. 286-296 (2006)
8. Vidal, R., Singaraju, D.: A closed-form solution to direct motion segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 510-515 (2005)
9. Vidal, R., Ravichandran, A.: Optical flow estimation and segmentation of multiple moving dynamic textures. In: IEEE Conference on Computer Vision and Pattern Recognition (2005)
10. Fan, X., Vidal, R.: The space of multibody fundamental matrices: Rank, geometry and projection. In: IEEE International Conference on Computer Vision (2005)
11. Yan, J., Pollefeys, M.: Articulated motion segmentation using ransac with priors. In: IEEE International Conference on Computer Vision (2005)
12. Hajder, L., Chetverikov, D.: Robust 3d segmentation of multiple moving objects underweak perspective. In: IEEE International Conference on Computer Vision (2005)
13. Shi, F., Wang, J., Zhang, J., Liu, Y.: Motion segmentation of multiple translating objects using line correspondences. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 315-320 (2005)
14. Zhang, J., Shi, F., Liu, Y.: Motion segmentation by multibody trifocal tensor using line correspondence. In: International Conference on Pattern Recognition (2006)
15. Faugeras, O., Navab, N., Deriche, R.: On the information contained in the motion field of lines and the cooperation between motion and stereo. International Journal of Imaging Systems and Technology (1991)
16. Jiang, S.F., Chen, Z., Yang, S.H.: Reconstructing 3d rotation motion parameters from 2d image straight-line optical flow. Journal of Nanchang Institute of Aeronautical Technology(Natural Science) (2005)
17. Hartley, R., Vidal, R.: The multibody trifocal tensor: Motion segmentation from 3 perspective views. In: IEEE Conference on Computer Vision and Pattern Recognition (2004)