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ELITE: A goal oriented vision system for moving objects detection

Published online by Cambridge University Press:  09 March 2009

N. A. Borghese ,
M. Di Rienzo ,
G. Ferrigno  and
A. Pedotti
N. A. Borghese
Affiliation:
Centro di Bioingegneria, Fondazione Pro Juventute, Politecnico Milano, Via Gozzadini 7, 20148 Milano; and Istituto di Fisiologia dei Centri Nervosi, CNR, Via Mario Bianco, 9 20131 Milano, (Italy)
M. Di Rienzo
Affiliation:
Centro di Bioingengeria, Fondazione Pro Juventute, Politecnico Milano, Via Gozzadini 7, 20148 Milano (Italy).
G. Ferrigno
Affiliation:
Centro di Bioingengeria, Fondazione Pro Juventute, Politecnico Milano, Via Gozzadini 7, 20148 Milano (Italy).
A. Pedotti
Affiliation:
Centro di Bioingengeria, Fondazione Pro Juventute, Politecnico Milano, Via Gozzadini 7, 20148 Milano (Italy).
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Summary

A specially designed system for movement monitoring is here presented. The system has a two level architecture. At the first level, a hardware processor analyses in real-time the images provided by a set of standard TV cameras and, using a technique based on the convolution operator, recognizes in each frame objects that have a specific shape. The coordinates of these objects are fed to a computer, the second level of the system, that analyses the movement of these objects with the aid of a set of rules representing the knowledge of the context. The system was extensively tested on the field and the main results are reported.

The whole system can work as a controlling device in robotics or as a general real-time image processor as well as an automatic movement analyser in biomechanics, orthopedic and neurological medicine.

Keywords

ELITE: Vision systemMoving objectsRobot controlMovement analyser

Information

Type
Article
Information
Robotica , Volume 9 , Issue 3 , July 1991 , pp. 275 - 282
Copyright
Copyright © Cambridge University Press 1991

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References

1.Marr, D., “Early Processing of Visual Information” A.I. Memo 340 (M.I.T. Artificial Intelligence Laboratory, Cambridge, 1975).Google Scholar
2.Marr, D., Vision, (Freeman, San Francisco CA, 1982).Google Scholar
3.Livingstone, M.S. and Hubel, D.H., “Connections between leyer 4B of Area 17 and the thick cytochrome Oxidase Stripes of Area 18 in the Squirrel Monkey” J. Neuroscience 7 (11), 3371–3377 (1987).CrossRefGoogle Scholar
4.Van Essen, D.C. and Maunsell, J.H.R., “Hierarchical Organization and Functional Streams in the Visual Cortex” Trends in Neurosciences TINS 6, No. 9, 370–375 (1983).Google Scholar
5.Ullman, S., The Interpretation of Visual Motion, (M.I.T. Press, Cambridge, MA, 1979).Google Scholar
6.Rumelhart, D., McClelland, J. and the PDP Research Group, PDP Parallel Distributed Processing vols. 1, 2 (MIT Press Cambridge, MA, 1986).CrossRefGoogle Scholar
7.Kittler, J. and Duff, M.J.B. (eds.), Image Processing System Architectures (Research Studies Press, Letchworth, UK, 1985).Google Scholar
8.Duff, M.J.B. and Levialdi, S. (eds.), Languages and Architectures for Image Processings (Academic Press, New York, 1981).Google Scholar
9.Fu, K.S. and Ichikawa, T. (eds.), Special Computer Architectures for Pattern Processing (CRC Press, London, 1982).Google Scholar
10.Bullock, B.L., Computer Vision Systems (Academic Press, New York, 1978).Google Scholar
11.Jarvis, R.A., “Application-oriented Robotic Vision, a review” Robotica 2, part 1, 3–15 (1983).Google Scholar
12.Nishihara, H.K. and Larson, N.G., “Towards Real-Time Implementation of the Marr-Poggio stereo-matcher” Proc. Image Understanding Workshop (edited by Lee Baumann, 1981).Google Scholar
13.Barlow, H.B. and Levick, R.W., “The mechanism of directionally selective units in rabbit's retina” J. Physiol. 178, 477–504 (1965).Google Scholar
14.Williams, D.R., “Seeing through the photoreceptor mosaic” Trends in Neuroscience TINS 9, No. 5, 204–211 (1986).Google Scholar
15.Koch, C., Poggio, T. and Torre, V., “Computations in the vertebrate retina: gain enhancement, differentiation and motion discrimination” Trends in Neuroscience TINS 9, No. 5, 204–211 (1986).CrossRefGoogle Scholar
16.Ferrigno, G. and Pedotti, A., “ELITE: A Digital Dedicated Hardware System for Movement Analysis Via Real-Time TV Signal Processing” IEEE Trans. Biom. Eng. BME 32, 943–949 (1985).Google Scholar
17.Oppenheim, A.V. and Schafer, R.M., Digital Signal Processing (Prentice Hall, Englewood Cliffs, N.J., USA, 1975).Google Scholar
18.Marr, D. and Hildreth, E.C., “Theory of Edge detection” Proc. Roy. Soc. London B 207, 187–217 (1980).Google ScholarPubMed
19.Hildreth, E.C. and Koch, C., “The analysis of Visual Motion: from computational theory to neuronal Mechanisms” Ann. Rev. Neurosci. 10, 477–533 (1987).Google Scholar
20.Yuille, A.L. and Poggio, T.A., “Scaling Theorems for Zero Crossing” IEEE Trans, on Patt. Anal, and Mach. Intell. PAMI-8, No. 1, 15–25 (1986).Google Scholar
21.Borghese, N.A., Ferrigno, G. and Pedotti, A., “3D Movement Detection: A Hierarchical Approach” Proc. 1988 IEEE International Conference on Systems, Man, and Cybernetics” 1 (International Academic Publishers, Pergamon Press, Beijing 100044, China, 1988) pp. 303–306.Google Scholar
22.Borghese, N.A. and Ferrigno, G., “A Knowledge based system for automatic movement tracking” In; Expert Systems; theory and applications, Proceedings IASTED International Symposium Geneva, CH (June, 1987) (Acta Press, Calgary, Alberta, Canada T2M 4L8, 1987) pp. 225–227.Google Scholar