Range flow for varying illumination

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

Volumn 5302 LNCS, Issue PART 1, 2008, Pages 509-522

  Schuchert, Tobias ^a   Aach, Til ^b   Scharr, Hanno ^a  

^a FORSCHUNGSZENTRUM JÜLICH   (Germany)

^b RWTH AACHEN UNIVERSITY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; VELOCITY;

BRIGHTNESS CONSTANCY CONSTRAINT; BRIGHTNESS CONSTANCY MODELS; FLOW ESTIMATION; GRADIENT CONSTANCY MODELS; HOMOMORPHIC FILTERING; INTENSITY IMAGES; OPTICAL FLOW ESTIMATION; PERFORMANCE TESTS;

LUMINANCE;

EID: 56749180617     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-88682-2_39     Document Type: Conference Paper

References (29)

1. Haußecker, H., Fleet, D.J.: Computing optical flow with physical models of brightness variation. PAMI 23, 661-673 (2001)
2. Schuchert, T., Scharr, H.: Simultaneous estimation of surface motion, depth and slopes under changing illumination. In: Hamprecht, F.A., Schnörr, C., Jähne, B. (eds.) DAGM 2007. LNCS, vol. 4713, pp. 184-193. Springer, Heidelberg (2007)
3. Simoncelli, E.P.: Design of multi-dimensional derivative filters. In: ICIP (1), pp. 790-794 (1994)
4. Scharr, H.: Optimal filters for extended optical flow. In: International Workshop on Complex Motion, pp. 14-29 (2004)
5. Lucas, B., Kanade, T.: An iterative image registration technique with an application to stereo vision. In: DARPA Im. Underst. Workshop, pp. 121-130 (1981)
6. Bigün, J., Granlund, G., Wiklund, J.: Multidimensional orientation estimation with applications to texture analysis and optical flow. IEEE Trans. PAMI 13, 775-790 (1991)
7. Bruhn, A., Weickert, J., Schnörr, C.: Lucas/kanade meets horn/schunck: Combining local and global optic flow methods. IJCV 61, 211-231 (2005)
8. Black, M.J., Anandan, P.: The robust estimation of multiple motions: parametric and piecewise-smooth flow fields. Comput. Vis. Image Underst. 63, 75-104 (1996)
9. Ju, S.X., Black, M.J., Jepson, A.D.: Skin and bones: Multi-layer, locally affine, optical flow and regularizaron with transparency. In: Proc. Computer Vision and Pattern Recognition, CVPR-1996, San Francisco, pp. 307-314 (1996)
10. Yamamoto, M., Boulanger, P., Beraldin, J.A., Rioux, M.: Direct estimation of range flow on deformable shape from a video rate range camera. IEEE PAMI 15, 82-89 (1993)
11. Gharavi, H., Gao, S.: 3-d motion estimation using range data. IEEE Transactions on intelligent transportation systems 8, 133-143 (2007)
12. Spies, H., Haußecker, H., Jähne, B., Barron, J.: Differential range flow estimation. In: DAGM, pp. 309-316 (1999)
13. Spies, H., Jähne, B., Barron, J.: Range flow estimation. CVIU 85, 209-231 (2002)
14. Zhang, Y., Kambhamettu, C.: Integrated 3d scene flow and structure recovery from multiview image sequences. In: CVPR, pp. 2674-2681 (2000)
15. Vedula, S., Baker, S., Rander, P., Collins, R., Kanade, T.: Three-dimensional scene flow. IEEE PAMI 27, 475-480 (2005)
16. Scharr, H.: Towards a multi-camera generalization of brightness constancy. In: Jähne, B., Mester, R., Barth, E., Scharr, H. (eds.) IWCM 2004. LNCS, vol. 3417, pp. 78-90. Springer, Heidelberg (2007)
17. Barron, J., Fleet, D., Beauchemin, S.: Performance of optical flow techniques. IJCV 12(1), 43-77 (1994)
18. Jähne, B., Haußecker, H., Geissler, P.: Handbook of Computer Vision and Applications, 1st edn. Academic Press, London (1999)
19. Bruhn, A.: Variational optic flow computation, accurate modelling and efficient numerics (2006)
20. Papenberg, N., Bruhn, A., Brox, T., Didas, S., Weickert, J.: Highly accurate optic flow computation with theoretically justified warping. IJCV 67, 141-158 (2006)
21. Denney, T.S.J., Prince, J.L.: Optimal brightness functions for optical flow estimation of deformable motion. IEEE Trans. Im. Proc. 3, 178-191 (1994)
22. Toth, D., Aach, T., Metzler, V.: Illumination-invariant change detection. In: SSIAI, pp. 3-7 (2000)
23. Oppenheim, A., Schafer, R., Stockham, T.G.: Nonlinear filtering of multiplied and convolved signals. In: Proceedings of the IEEE, vol. 56, pp. 1264-1291 (1968)
24. Pons, J.P., Keriven, R., Faugeras, O.: Multi-view stereo reconstruction and scene flow estimation with a global image-based matching score. IJCV 72(2), 179-193 (2007)
25. Huguet, F., Devernay, F.: A variational method for scene flow estimation from stereo sequences. In: ICCV (2007)
26. Li, R., Sclaroff, S.: Multi-scale 3d scene flow from binocular stereo sequences. wacvmotion 2, 147-153 (2005)
27. Jähne, B.: Digitale Bildverarbeitung, 4th edn. Springer, Heidelberg (1997)
28. Scharr, H., Schuchert, T.: Simultaneous motion, depth and slope estimation with a camera-grid. In: Vision, Modeling and Visualization 2006, pp. 81-88 (2006)
29. Spies, H., Jähne, B., Barron, J.L.: Surface expansion from range data sequences. In: Radig, B., Florczyk, S. (eds.) DAGM 2001. LNCS, vol. 2191, pp. 163-169. Springer, Heidelberg (2001)