Abstract
Early vision is dominated by image patches or features derived from them; high-level vision is dominated by shape representation and recognition. However there is almost no work between these two levels, which creates a problem when trying to recognize complex categories such as “airports” for which natural feature clusters are ineffective. We argue that an intermediate-level representation is necessary and that it should incorporate certain high-level notions of distance and geometric arrangement into a form derivable from images. We propose an algorithm based on a reaction-diffusion equation that meets these criteria; we prove that it reveals (global) aspects of the distance map locally; and illustrate its performance on airport and other imagery, including visual illusions.
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
Lowe, D.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60, 91–110 (2004)
Fidler, S., Leonardis, A.: Towards scalable representations of object categories: Learning a hierarchy of parts. In: CVPR. IEEE Computer Society (2007)
Ferrari, V., Jurie, F., Schmid, C.: From images to shape models for object detection. International Journal of Computer Vision 87, 284–303 (2010)
Opelt, A., Pinz, A., Zisserman, A.: A boundary-fragment-model for object detection. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006, Part II. LNCS, vol. 3952, pp. 575–588. Springer, Heidelberg (2006)
Opelt, A., Pinz, A., Zisserman, A.: Learning an alphabet of shape and appearance for multi-class object detection. International Journal of Computer Vision 80, 16–44 (2008)
Ullman, S., Epshtein, B.: Visual classification by a hierarchy of extended fragments. In: Ponce, J., Hebert, M., Schmid, C., Zisserman, A. (eds.) Toward Category-Level Object Recognition. LNCS, vol. 4170, pp. 321–344. Springer, Heidelberg (2006)
Siddiqi, K., Shokoufandeh, A., Dickinson, S.J., Zucker, S.W.: Shock graphs and shape matching. International Journal of Computer Vision 35, 13–32 (1999)
McKeown, D.M., Harvey, W.A., McDermott, J.: Rule-based interpretation of aerial imagery. IEEE Trans. Pattern Anal. Mach. Intell. 7, 570–585 (1985)
Borenstein, E., Ullman, S.: Combined top-down/bottom-up segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 30, 2109–2125 (2008)
Florack, L., ter Haar Romeny, B., Viergever, M., Koenderink, J.: The gaussian scale-space paradigm and the multiscale local jet. 18, 61–75 (1996)
Dimitrov, P., Zucker, S.W.: A constant production hypothesis that predicts the dynamics of leaf venation patterning. Proc. Nat. Acad. Sci (USA) 13, 9363–9368 (2006)
Courant, R., Hilbert, D.: Methods of mathematical physics, vol. 2. Interscience (1962)
Koenderink, J.: The structure of images. Biological Cybernetics 50, 363–370 (1984)
Belkin, M., Niyogi, P.: Laplacian eigenmaps for dimensionality reduction and data representation. Neural Computation 6, 1373–1396 (2003)
Coifman, R., Lafon, S., Lee, A., Maggioni, M., Nadler, B., Warner, F., Zucker, S.: Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps. Proc. Nat. Acad. Sci. (USA) 102, 7426–7431 (2005)
Murray, S.O., Boyaci, H., Kersten, D.: The representation of perceived angular size in human primary visual cortex. Nature Neurosci. 9, 429–434 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Dimitrov, P., Lawlor, M., Zucker, S.W. (2012). Distance Images and Intermediate-Level Vision. In: Bruckstein, A.M., ter Haar Romeny, B.M., Bronstein, A.M., Bronstein, M.M. (eds) Scale Space and Variational Methods in Computer Vision. SSVM 2011. Lecture Notes in Computer Science, vol 6667. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24785-9_55
Download citation
DOI: https://doi.org/10.1007/978-3-642-24785-9_55
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24784-2
Online ISBN: 978-3-642-24785-9
eBook Packages: Computer ScienceComputer Science (R0)