Abstract
Building on our recent hierarchical model of object recognition in cortex, we show how this model can be extended in a straightforward fashion to perform basic-level object categorization. We demonstrate the capability of our scheme, called “Categorical Basis Functions” (CBF) with the example domain of cat/dog categorization, using stimuli generated with a novel 3D morphing system. We also contrast CBF to other schemes for object categorization in cortex, and present preliminary results from a physiology experiment that support CBF.
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
Biederman, I. (1987). Recognition-by-components: A theory of human image understanding. Psych. Rev. 94, 115–147.
Bülthoff, H. and Edelman, S. (1992). Psychophysical support for a two-dimensional view interpolation theory of object recognition. Proc. Nat. Acad. Sci. USA 89, 60–64.
Edelman, S. (1999). Representation and Recognition in Vision. MIT Press, Cambridge, MA.
Freedman, D., Riesenhuber, M., Shelton, C., Poggio, T., and Miller, E. (1999). Categorical representation of visual stimuli in the monkey prefrontal (PF) cortex. In Soc. Neurosci. Abs., volume 29, 884.
Gauthier, I., Anderson, A., Tarr, M., Skudlarski, P., and Gore, J. (1997). Levels of categorization in visual recognition studied with functional mri. Curr. Biol. 7, 645–651.
Intrator, N. and Edelman, S. (1997). Learning low-dimensional representations via the usage of multiple-class labels. Network 8, 259–281.
Logothetis, N., Pauls, J., and Poggio, T. (1995). Shape representation in the inferior temporal cortex of monkeys. Curr. Biol. 5, 552–563.
Marr, D. (1982). Vision: a computational investigation into the human representation and processing of visual information. Freeman, San Francisco, CA.
Papageorgiou, C., Oren, M., and Poggio, T. (1998). A general framework for object detection. In Proceedings of the International Conference on Computer Vision, Bombay, India, 555–562. IEEE, Los Alamitos, CA.
Perrett, D., Oram, M., Harries, M., Bevan, R., Hietanen, J., Benson, P., and Thomas, S. (1991). Viewer-centred and object-centred coding of heads in the macaque temporal cortex. Exp. Brain Res. 86, 159–173.
Poggio, T. and Edelman, S. (1990). A network that learns to recognize 3D objects. Nature 343, 263–266.
Quinn, P., Eimas, P., and Rosenkrantz, S. (1993). Evidence for representations of perceptually similar natural categories by 3-month-old and 4-month-old infants. Perception 22, 463–475.
Riesenhuber, M. and Poggio, T. (1999). Are cortical models really bound by the “Binding Problem”? Neuron 24, 87–93.
Riesenhuber, M. and Poggio, T. (1999). Hierarchical models of object recognition in cortex. Nature Neurosci. 2, 1019–1025.
Riesenhuber, M. and Poggio, T. (1999). A note on object class representation and categorical perception. Technical Report AI Memo 1679, CBCL Paper 183, MIT AI Lab and CBCL, Cambridge, MA.
Rosch, E. (1973). Natural categories. Cognit. Psych. 4, 328–350.
Shelton, C. (1996). Three-dimensional correspondence. Master’s thesis, MIT, (1996).
Tarr, M. (1995). Rotating objects to recognize them: A case study on the role of viewpoint dependency in the recognition of three-dimensional objects. Psychonom. Bull. & Rev. 2, 55–82.
Tarr, M. and Gauthier, I. (1998). Do viewpoint-dependent mechanisms generalize across members of a class? Cognition 67, 73–110.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Riesenhuber, M., Poggio, T. (2000). CBF: A New Framework for Object Categorization in Cortex. In: Lee, SW., Bülthoff, H.H., Poggio, T. (eds) Biologically Motivated Computer Vision. BMCV 2000. Lecture Notes in Computer Science, vol 1811. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45482-9_1
Download citation
DOI: https://doi.org/10.1007/3-540-45482-9_1
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67560-0
Online ISBN: 978-3-540-45482-3
eBook Packages: Springer Book Archive