Rapid inference of object rigidity and reflectance using optic flow

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

Volumn 5702 LNCS, Issue , 2009, Pages 881-888

  Zang, Di ^a   Doerschner, Katja ^b   Schrater, Paul R ^a  

^a UNIVERSITY OF MINNESOTA   (United States)

^b BILKENT UNIVERSITY   (Turkey)

Author keywords

Optic flow; Reflectance classification; Rigidity detection; Specular motion

Indexed keywords

ACROSS TIME; DIFFUSE SURFACES; GLOBAL TRANSFORMATION; KEY OBJECT; MOTION RECONSTRUCTION; MOVING SURFACES; NON-RIGID OBJECTS; OBJECT SHAPE; OPTIC FLOW; PROCRUSTES ANALYSIS; REFLECTANCE CLASSIFICATION; REFLECTIVE SURFACES; RELATIVE MOTION; RIGID OBJECTS; SPECULAR MOTION; STRUCTURE FROM MOTION;

IMAGE ANALYSIS; REFLECTION; RIGIDITY;

THREE DIMENSIONAL;

EID: 70349314880     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-03767-2_107     Document Type: Conference Paper

References (17)

1. Hartley, R.I., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, Cambridge (2004)
2. Zisserman, A., Giblin, P., Blake, A.: The information available to a moving observer from specularities. IVC 7(1), 38-42
3. Roth, S., Black, M.J.: Specular flow and the recovery of surface structure. In: CVPR 2006: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 1869-1876 (2006)
4. Adato, Y., Vasilyev, Y., Ben Shahar, O., Zickler, T.: Toward a theory of shape from specular flow. In: ICCV 2007, pp. 1-8 (2007)
5. Vasilyev, Y., Adato, Y., Zickler, T., Ben Shahar, O.: Dense specular shape from multiple specular flows. In: CVPR 2008, pp. 1-8 (2008)
6. Healey, G., Binford, T.: Local shape from specularity. CVGIP 42(1), 62-86 (1988)
7. Bhat, D., Nayar, S.: Binocular stereo in the presence of specular reflection. In: ARPA 1994, pp. 1305-1315 (1994)
8. Saito, M., Kashiwagi, H., Sato, Y., Ikeuchi, K.: Measurement of surface orientations of transparent objects using polarization in highlight. In: Proc. of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, p. 1381 (1999)
9. Lin, S., Li, Y., Kang, S.B., Tong, X., Shum, H.-Y.: Diffuse-specular separation and depth recovery from image sequences. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2352, pp. 210-224. Springer, Heidelberg (2002)
10. Lellmann, J., Balzer, J., Rieder, A., Beyerer, J.: Shape from specular reflection and optical flow. International Journal of Computer Vision 80(2), 226-241 (2008)
11. Chow, S.K., Chan, K.L.: Removal of specular reflection component using multiview images and 3d object model. In: Wada, T., Huang, F., Lin, S. (eds.) PSIVT 2009. LNCS, vol. 5414, pp. 999-1009. Springer, Heidelberg (2009)
12. Oren, M., Nayar, S.: A theory of specular surface geometry. International Journal of Computer Vision 24(2), 105-124 (1997)
13. Barron, J.L., Fleet, D.J., Beauchemin, S.S.: Performance of optical flow techniques. International Journal of Computer Vision 12(1), 43-77 (1994)
14. Tomasi, C., Kanade, T.: Shape and motion from image streams under orthography: a factorization method. International Journal of Computer Vision 9(2), 137-154 (1992)
15. Gower, J., Dijksterhuis, G.: Procrustes Problems. Oxford University Press, Oxford (2004)
16. Gonzalez, R.C., Woods, R.E.: Digital Image Processing. Addison-Wesley, Reading (1992)
17. Bruhn, A., Weickert, J., Schnörr, C.: Lucas/Kanade meets Horn/Schunck: Combining local and global optic flow methods. International Journal of Computer Vision 61(3), 211-231 (2005)