Abstract
This paper presents an integrated framework for vision that includes early, intermediate and high level components. It has been developed as a result of a substantial amount of study of each level of the problem. One of the goals of the work is to use this framework as the perception component of a mobile, task- driven robot. The novel aspects of the model include a significant top-down component, motivated both by recent biological observations as well as issues of computational complexity, a new definition of intermediate level vision based on the idea of aggregation and that permits both task-directed and bottom-up analysis modes, and temporal integration of recognition results over image sequences. Implementations of each part have been tested with good results; current work is focussing on extensions to the theoretical aspects of each of the three levels of vision as well as investigations into their integration into a single system.
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
Barrow, H., & Tenenbaum, J.M. (1978). Recovering intrinsic scene characteristics from images, in Computer vision systems, 3–26, A. Hanson and E. Riseman (Ed.), Academic Press, New York.
Burt, P. & Adelson, E. (1983). The laplacian pyramid as a compact image code, IEEE Transactions on Communications 31-4, 532–540.
Fleet, D., Hallett, P. & Jepson, A. (1985). Spatio-temporal inseparability in early visual processing, Biological Cybernetics 52, 153–164.
Fleet, D., & Jepson, A., (to appear) Hierarchical construction of orientation and velocity selective filters, IEEE Transactions on Pattern Analysis and Machine Intelligence.
Haenny, P., Schiller, P., (1988). State dependent activity in money visual cortex I. Single cell activity in V1 and V4 on visual tasks, Experimental brain Research 69, 225–244.
Haenny, P., Maunsell, J., & Schiller, P., (1988). State dependent activity in monkey visual cortex II. Retinal and extraretinal factors in V4, Experimental Brain Research 69, 245–259.
Heeger, D., (1988) Optical flow using spatiotemporal filters, International Journal of Computer Vision 1-4, p279–302.
Helmholtz, H. von, (1925). Hanbuch der physiologischenOptik, English translation Southall, J.
Hubel, D. & Wiesel, T. (1977). Functional architecture of macaque visual cortex, Proceedings of the Royal Society of London B 198, 1–59.
Jenkin, M., Jepson, A., and Tsotsos, J.K., (to appear) Techniques for Disparity Measurement, Computer Vision, Graphics, and Image Processing.
Jenkin, M., and Tsotsos, John K., (1986) Applying Temporal Constraints to the Dynamic Stereo Problem, Computer Vision, Graphics, and Image Processing 33, p 16–32.
Jenkin, M.R.M. (1988) Visual Stereoscopic Computation, Doctoral Dissertation, Department of Computer Science, University of Toronto.
Jepson, A.D., and Jenkin, M.R.M, (1989) The Fast Computation of Disparity from Phase Differences, CVPR 89, San Diego, California, p398–403.
Marr, D. (1982). Vision, W. H. Freeman, San Francisco.
Maunsell, J., & Newsome, W., (1987). Visual processing in monkey extrastriate cortex, Annual Review of Neuroscience 10, 363–401.
Maunsell, J., Sclar, G., & Nealey, T., (1988). Task-Specific signals in area V4 of monkey visual cortex, Proc. Society of Neuroscience, Toronto.
Moran, J. & Desimone, R. (1985). Selective attention gates visual processing in the extrastriate cortex, Science 229, 782–784.
Motter, B., (1988). Responses of visual cortical neurons during a focal attentive task, Proc. Society of Neuroscience, Toronto.
Mountcastle, V., Motter, B., Steinmetz, M., Sestokas, A., (1987). Common and differential effects of attentive fixation on the excitability of parietal and prestriate (V4) cortical visual neurons in the macaque monkey, Journal of Neuroscience 7-7, 2239–2255.
Neisser, U., (1967). Cognitive psychology, Appleton-Century-Crofts, New York.
Parasuraman, R., Davies, D., (editors) (1984). Varieties of attention, Academic Press, Orlando, FL.
Rabbitt, P. (1978). Sorting, categorization and visual search, in The Handbook of Perception: Perceptual processing, Vol. IX, edited by E. Carterette and M. Freidman, Academic Press, New York.
Shavit, E., (1989) A Prototype for motion processing in the extrastriate cortex, M.Sc. Thesis, Department of Computer Science, University of Toronto.
Shavit, E., and Tsotsos, J.K., (submitted) A Proposal for intermediate level vision: A case study in motion processing, 6th Israeli Conference on Vision and AI, Jerusalem, 1989.
Spitzer, H., Desimone, R., Moran, T., (1988). Both behavioral and neuronal performance are improved by increased attention, Proc. Society for Neuroscience, Toronto.
Treisman, A., & Gormican, S., (1988). Feature analysis in early vision: Evidence from search asymmetries, Psychological Review 95-1, 15–48.
Treisman, A., (1988). Features and objects: The fourteenth Bartlett memorial lecture, The Quarterly Journal of Experimental Psychology 40A-2, 201–237.
Treisman, A., & Sato, S., (1988). Conjunction search revisited, (submitted).
Tsotsos, J.K., Mylopoulos, J., Covvey, H., Zucker, S., (1980) A Framework for visual motion understanding, IEEE Pattern Analysis and Machine Intelligence 2-6, p563–573.
Tsotsos, J.K., (1985) Knowledge Organization and its role in the interpretation of time-varying data: The ALVEN system, Computational Intelligence 1–1, p16–32.
Tsotsos, J. (1987a). Representational axes and temporal cooperative processes, in Vision, brain and cooperative computation, 361–418, M. Arbib and A. Hansen (Ed.), MIT Press / Bradford Books, Cambridge, Massachusetts.
Tsotsos, J.K., (1988) A complexity level analysis of immediate vision, International Journal of Computer Vision 1-4, p303–320.
Tsotsos, J., (to appear). Analyzing vision at the complexity level, The Behavioral and Brain Sciences.
Tsotsos, J. (1987b). Image understanding, in The encyclopedia of artificial intelligence, 389–409, S. Shapiro (Ed.), John Wiley & Sons, New York.
Tsotsos, J.K., (1989) The complexity of perceptual search tasks, Proceedings International Joint Conference on Artificial Intelligence, Detroit, August 1989.
Watson, A. & Ahumada, A. (1987). An orthogonal oriented quadrature hexagonal image pyramid, NASA Technical Memorandum 100054.
Wolfe, J., Cave, K., Yu, K., (1988). Directing attention to complex objects, Proc. Society for neuroscience, Toronto.
Zucker, S. (1987). Early vision, in The encyclopedia of artificial intelligence, 1131–1152, S. Shapiro (Ed.), John Wiley & Sons, New York.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1992 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Tsotsos, J.K. (1992). Motion Understanding Systems. In: Sood, A.K., Wechsler, H. (eds) Active Perception and Robot Vision. NATO ASI Series, vol 83. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-77225-2_1
Download citation
DOI: https://doi.org/10.1007/978-3-642-77225-2_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-77227-6
Online ISBN: 978-3-642-77225-2
eBook Packages: Springer Book Archive