Abstract
Rigidity and reflectance are key object properties, important in their own rights, and they are key properties that stratify motion reconstruction algorithms. However, the inference of rigidity and reflectance are both difficult without additional information about the object’s shape, the environment, or lighting. For humans, relative motions of object and observer provides rich information about object shape, rigidity, and reflectivity. We show that it is possible to detect rigid object motion for both specular and diffuse reflective surfaces using only optic flow, and that flow can distinguish specular and diffuse motion for rigid objects. Unlike nonrigid objects, optic flow fields for rigid moving surfaces are constrained by a global transformation, which can be detected using an optic flow matching procedure across time. In addition, using a Procrustes analysis of structure from motion reconstructed 3D points, we show how to classify specular from diffuse surfaces.
This work has been supported in part by the European Commission Seventh Framework Programme Marie Curie International Reintegration Grant IRG-239494.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Hartley, R.I., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, Cambridge (2004)
Zisserman, A., Giblin, P., Blake, A.: The information available to a moving observer from specularities. IVC 7(1), 38–42
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)
Adato, Y., Vasilyev, Y., Ben Shahar, O., Zickler, T.: Toward a theory of shape from specular flow. In: ICCV 2007, pp. 1–8 (2007)
Vasilyev, Y., Adato, Y., Zickler, T., Ben Shahar, O.: Dense specular shape from multiple specular flows. In: CVPR 2008, pp. 1–8 (2008)
Healey, G., Binford, T.: Local shape from specularity. CVGIP 42(1), 62–86 (1988)
Bhat, D., Nayar, S.: Binocular stereo in the presence of specular reflection. In: ARPA 1994, pp. 1305–1315 (1994)
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)
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)
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)
Chow, S.K., Chan, K.L.: Removal of specular reflection component using multi-view images and 3d object model. In: Wada, T., Huang, F., Lin, S. (eds.) PSIVT 2009. LNCS, vol. 5414, pp. 999–1009. Springer, Heidelberg (2009)
Oren, M., Nayar, S.: A theory of specular surface geometry. International Journal of Computer Vision 24(2), 105–124 (1997)
Barron, J.L., Fleet, D.J., Beauchemin, S.S.: Performance of optical flow techniques. International Journal of Computer Vision 12(1), 43–77 (1994)
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)
Gower, J., Dijksterhuis, G.: Procrustes Problems. Oxford University Press, Oxford (2004)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing. Addison-Wesley, Reading (1992)
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)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zang, D., Doerschner, K., Schrater, P.R. (2009). Rapid Inference of Object Rigidity and Reflectance Using Optic Flow. In: Jiang, X., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2009. Lecture Notes in Computer Science, vol 5702. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03767-2_107
Download citation
DOI: https://doi.org/10.1007/978-3-642-03767-2_107
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03766-5
Online ISBN: 978-3-642-03767-2
eBook Packages: Computer ScienceComputer Science (R0)