Abstract
We argue that human vision has natural timescales, and that models of human vision at these different timescales are qualitatively different. In particular, at the timescale of a few seconds, human vision can be modeled in terms of two primitive functional routines. A “what” routine determines object identity from a segmented input and a “Where” routine determines the retinal location of a desired object. More complicated functions can be composed from these two. In particular, a complicated visuo-motor task such as copying can be described in terms of these two routines. The primary subroutine needed is one that computes the relationship of the parts of an object with respect to an object-centered frame.
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Literatur
Ballard, D. H. and Wixson, L. E. (1993). Object recognition using steerable filters at multiple scales. In Proceedings of the IEEE Workshop on Qualitative Vision.
Freeman, W. T. and Adelson, E. H. (1991). The design and use of steerable filters. IEEE PAMI, 13(9):891–906.
Hinton, G. F. (1981). Shape recognition in parallel systems. In International Joint Conference on Artificial Intelligence, pages 1088–1096.
Kanerva, P. (1988). Sparse Distributed Memory. Cambridge, MA: Bradford Books.
Marr, D. (1982). Vision: A Computational Investigation into the Human Representation and Processing of Visual Information. San Francisco: W.H. EVeeman and Company.
Mulier, F. and Cherkassky, V. (1995). Self- organization as an iterative kernel smoothing process. To appear in Neural Computation.
Murase, H. and Nayar, S. (1993). Learning and recognition of 3-d objects from brightness images. Working Notes, AAAI Fall Symp, Series (Machine Learning in Computer Vision: What, Why, and How?), pages 25–29.
Newell, A. (1990). Unified Theories of Cognition. Cambrdige, MA: Harvard University Press.
Nowlan, S. J. (1990). Maximum likelihood competitive learning. In Advances in Neural Information Processing Systems 2, pages 574–582. Morgan Kaufmann
Pylyshyn, Z. (1993). Some primitive mechanisms underlying spatial attention. Technical Report RuCCS TR-8, Rutgers University.
Rao, R. P. and Ballard, D. H. (1995a). An active vision architecture based on iconic representations. To appear in AI Journal Special Issue on Vision.
Rao, R. P. and Ballard, D. H. (1995b). Learning saccadic eye movements using multiscale spatial filters. In Tesauro, G., Touretzky, D., and Leen, T., editors. Advances in Neural Information Processing Systems 7. Cambridge, MA: MIT Press.
Rao, R. P. and Ballard, D. H. (1995c). Object indexing using an iconic sparse distributed memory. Technical Report 559, Department of Computer Science, University of Rochester,.
Ritter, H., Martinetz, T., and Schulten, K. (1992). Neural Computation and Self-Organizing Maps: An Introduction. Reading, MA: Addison-Wesley.
Ullman, S. (1987). Visual routines. In Readings in Computer Vision: Issues, Problems, Principles, and Paradigms, pages 298–328. Los Altos, CA: Morgan Kaufmann Publishers, Inc.
Yair, E., Zeger, K., and Gersho, A. (1992). Competitive learning and soft competition for vector quantizer design. IEEE Trans. Signal Processing, 40(2):294–309.
Young, R. (1985). The Gaussian derivative theory of spatial vision: Analysis of cortical cell receptive field line-weighting profiles. General Motors Research Publication GMR-4920.
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© 1995 Springer-Verlag Berlin Heidelberg
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Ballard, D.H., Rao, R. (1995). A Computational Model of Human Vision Based on Visual Routines. In: Sagerer, G., Posch, S., Kummert, F. (eds) Mustererkennung 1995. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-79980-8_75
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DOI: https://doi.org/10.1007/978-3-642-79980-8_75
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