Abstract
It has become increasingly apparent that perception cannot be treated in isolation from the response generation, firstly because a very high degree of integration is required between different levels of percepts and corresponding response primitives. Secondly, it turns out that the response to be produced at a given instance is as much dependent upon the state of the system, as the percepts impinging upon the system. The state of the system is in consequence the combination of the responses produced and the percepts associated with these responses. Thirdly, it has become apparent that many classical aspects of perception, such as geometry, probably do not belong to the percept domain of a Vision system, but to the response domain.
There are not yet solutions available to all of these problems. In consequence, this overview will focus on what are considered crucial problems for the future, rather than on the solutions available today. It will discuss hierarchical architectures for combination of percept and response primitives, and the concept of combined percept-response invariances as important structural elements for Vision. It will be maintained that learning is essential to obtain the necessary flexibility and adaptivity. In consequence, it will be argued that invariances for the purpose of vision are not geometrical but derived from the percept-response interaction with the environment. The issue of information representation becomes extremely important in distributed structures of the types foreseen, where uncertainty of information has to be stated for update of models and associated data.
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References
D. Beymer and T. Poggio. Image Representations for Visual Learning. Science, 272:1905–1909, June 1996.
D. Gabor. Theory of communication. J. Inst. Elec. Eng., 93(26):429–457, 1946.
J.-H. Gao, L. M. Parsons, J. M. Bower, J. Xiong, J. Li, and P. T. Fox. Cerebellum Implicated in Sensory Acquisition and Discrimination Rather Than Motor Control. Science, 272:545–547, April 1996.
G. H. Granlund. In search of a general picture processing operator. Computer Graphics and Image Processing, 8(2):155–178, 1978.
G. H. Granlund. Integrated analysis-response structures for robotics systems. Report LiTH-ISY-I-0932, Computer Vision Laboratory, Linköping University, Sweden, 1988.
G. H. Granlund and H. Knutsson. Signal Processing for Computer Vision. Kluwer Academic Publishers, 1995. ISBN 0-7923-9530-1.
W. E. L. Grimson. Object Recognition by Computer: The Role of Geometric Constraints. MIT Press, Cambridge, MA. USA, 1990.
L. Haglund, H. Knutsson, and G. H. Granlund. Scale and Orientation Adaptive Filtering. In Proceedings of the 8th Scandinavian Conference on Image Analysis, Tromsö, Norway, May 1993. NOBIM. Report LiTH-ISY-I-1527, Linköping University.
R. Held and A. Hein. Movement-produced stimulation in the development of visually guided behavior. Journal of Comparative and Physiological Psychology, 56(5):872–876, October 1963.
R. I. G. Hughes. The structure and interpretation of quantum mechanics. Harvard University Press, 1989. ISBN: 0-674-84391-6.
L. Jacobsson and H. Wechsler. A paradigm for invariant object recognition of brightness, optical flow and binocular disparity images. Pattern Recognition Letters, 1:61–68, October 1982.
K. Kanatani. Camera rotation invariance of image characteristics. Computer Vision, Graphics and Image Processing, 39(3):328–354, Sept. 1987.
L. C. Katz and C. J. Shatz. Synaptic activity and the construction of cortical circuits. Science, 274:1133–1138, November 15 1996.
J. J. Koenderink and A. J. van Doorn. Invariant properties of the motion parallax field due to the movement of rigid bodies relative to an observer. Opt. Acta 22, pages 773–791, 1975.
J. J. Koenderink and A. J. van Doorn. The structure of images. Biological Cybernetics, 50:363–370, 1984.
T. Landelius. Behavior Representation by Growing a Learning Tree, September 1993. Thesis No. 397, ISBN 91-7871-166-5.
T. Landelius and H. Knutsson. A Dynamic Tree Structure for Incremental Reinforcement Learning of Good Behavior. Report LiTH-ISY-R-1628, Computer Vision Laboratory, S-581 83 Linköping, Sweden, 1994.
T. Landelius and H. Knutsson. Behaviorism and Reinforcement Learning. In Proceedings, 2nd Swedish Conference on Connectionism, pages 259–270, Skövde, March 1995.
T. Landelius and H. Knutsson. Reinforcement Learning Adaptive Control and Explicit Criterion Maximization. Report LiTH-ISY-R-1829, Computer Vision Laboratory, S-581 83 Linköping, Sweden, April 1996.
R. A. Lewitt. Physiological Psychology. Holt, Rinehart and Winston, 1981.
L. M. Lifshitz. Image segmentation via multiresolution extrema following. Tech. Report 87-012, University of North Carolina, 1987.
J. L. Mundy and A. Zisserman, editors. Geometric Invariance in Computer Vision. The MIT Press, Cambridge, MA. USA, 1992. ISBN 0-262-13285-0.
K. Nordberg, G. Granlund, and H. Knutsson. Representation and Learning of Invariance. In Proceedings of IEEE International Conference on Image Processing, Austin, Texas, November 1994. IEEE.
T. Poggio and S. Edelman. A network that learns to recognize three-dimensional objects. Nature, 343:263–266, 1990.
J. L. Raymond, S. G. Lisberger, and M. D. Mauk. The Cerebellum: A Neuronal Learning Machine? Science, 272:1126–1131, May 1996.
G. M. Shepherd. The Synaptic Organization of the Brain. Oxford University Press, 2nd edition, 1979.
S. Ullman and R. Basri. Recognition by linear combinations of models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(10):992–1006, 1991.
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Granlund, G.H. (1997). From multidimensional signals to the generation of responses. In: Sommer, G., Koenderink, J.J. (eds) Algebraic Frames for the Perception-Action Cycle. AFPAC 1997. Lecture Notes in Computer Science, vol 1315. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0017859
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DOI: https://doi.org/10.1007/BFb0017859
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