Abstract
Studies on visual perception have demonstrated that selective attention mechanisms and space-variant sensing are powerful tools for focusing available computing resources to the process of relevant data. In this paper an overall architecture for an active, anthropomorphic robot vision system which integrates retina-like sensing and attention mechanisms is proposed. Gaze direction is shifted both on the basis of sensory and semantic characteristics of the visual input, which are extracted separately by means of a parallel and serial analysis. An implementation of the system by means of optical flow and neural network techniques is described, and the results of its application are discussed.
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
J. Aloimonos, I. Weiss, and A. Bandyopadhyay. Active vision. International Journal of Computer Vision 1(4), pp. 333–356, 1988.
Y. Aloimonos. Purposive and qualitative active vision. In: “Artificial Intelligence and Computer Vision”, Y.A. Feldman and A. Bruckstein eds., Elsevier, 1991.
R. Bajcsy. Active perception. Proc. of the IEEE 76(8), pp. 996–1005, 1988.
D.H. Ballard. Animate vision. Artificial Intelligence 48, pp. 57–86, 1991.
F. Bartolini, V. Cappellini, C. Colombo, and A. Mecocci. Multiwindow least squares approach to the estimation of optical flow with discontinuities. Optical Engineering, 32(6), pp. 1250–1256, 1993.
P.J. Burt and E.H. Adelson. The Laplacian pyramid as a compact image code. IEEE Transactions on Communications 31(4), pp. 532–540, 1983.
P.J. Burt. Smart sensing within a pyramid vision machine, Proc, of the IEEE 76(8), pp. 1006–1015, 1988.
R. Cipolla and A. Blake. Surface orientation and time to contact from image divergence and deformation. Proc. 2nd European Conference on Computer Vision, pp. 187–202, S. Margherita Ligure (Italy) 1992.
J.J. Clark and N.J. Ferrier. Attentive visual servoing. In: “Active vision”, A. Blake and A. Yuille eds., MIT Press, 1992.
J.L. Crowley. A representation for visual information. Tech. Rep. CMU-RI-TR-82-7, Carnegie-Mellon University, 1987.
S.M. Culhane and J.K. Tsotsos. An attentional prototype for early vision. Proc. 2nd European conference on Computer Vision, pp. 551–560, S. Margherita Ligure (Italy) 1992.
D.M. De Micheli, M. Bergamasco, and P. Dario. An anthropomorphic active vision system based on a retina-like sensor. Proc. 3rd International Symposium on Measurement and Control in Robotics, Torino (Italy) September 1993.
R. Hect-Nielsen. Applications of the counter-propagation networks. Neural Networks 2(1), 1988.
H. von Helmholtz. “Psychological optics”. J.P.C. Sothall ed., Dover, New York, 1866/ 1925.
B.K.P. Horn and B.G. Schunck. Determining optical flow. Artificial Intelligence 17, pp. 185–203, 1981.
R. Jain, S.L. Bartlett, and N. O’Brien. Motion stereo using ego-motion complex logarithmic mapping. IEEE Transactions on Pattern Analysis and Machine Intelligence 9(3), pp. 356–369, 1987.
R.C. Jain and T.O. Binford. Ignorance, myopia, and naiveté in computer vision systems. Computer Vision, Graphics and Image Processing: Image Understanding 53(1), pp. 112–117, 1991.
W. James. “The principles of psychology”, Harvard University Press, Cambridge, 1890/1983.
W.A. Johnston and V.J. Dark. Selective attention. Annual Review of Psychology 37, pp. 43–75, 1986.
K. Kanatani. “Group-theoretical methods in image understanding”, Springer, 1990.
C. Koch and S. Ullman. Shifts in selective visual attention: toward the underlying neural circuitry. In: “Matters of intelligence”. L.M. Vaina ed., D. Reidel Pub. Comp., 1987.
J.J. Koenderink and A.J. van Doom. Invariant properties of the motion parallax field due to the movement of rigid bodies relative to an observer. Optica Acta 22(9), pp. 773–791, 1975.
T. Kohonen. Self-organized formation of topologically correct feature maps. Biological Cybernetics 43, pp. 59–69, 1982.
J.L. Mundy and A. Zisserman. Projective geometry for machine vision. In: “Geometric invariance in computer vision”, J.L. Mundy and A. Zisserman eds., MIT Press, 1992.
K. Nakayama. The iconic bottleneck and the tenuous link between early visual processing and perception. In: “Vision: coding and efficiency”, C. Blakemore ed., University Press, 1991.
D. Noton and L. Stark. Eye movements and visual perception. Scientific American, 224(6), pp. 34–43, 1971.
B. Olshausen. A neural model of visual attention and invariant pattern recognition. Tech. Rep. CalTech, CNS Memo 18, September 1992.
M. Posner. Orienting of attention. Quarterly Journal of Experimental Psychology 32, pp. 3–25, 1980.
A. Rosenfeld et al. “Multiresolution image processing and analysis”, A. Rosenfeld ed., Springer, 1984.
M. Rucci and P. Dario. Selective attention mechanisms in a vision system based on neural networks. Proc. International Conference on Intelligent Robots and Systems, Yokohama (Japan) July 1993.
D.E. Rumelhart, G.E. Hinton, and R.J. Williams. Learning internal representations by error propagation. In: “Parallel Distributed Processing”, MIT Press, 1986.
G. Sandini and V. Tagliasco. An anthropomorphic retina-like structure for scene analysis. Computer Graphic and Image Processing 14(3), pp. 365–372, 1980.
G. Sandini and P. Dario. Active vision based on space-variant sensing. Proc. 5th International Symposium of Roboticsw Research, pp. 408-417, Tokio 1989.
E.L. Schwartz. Spatial mapping in the primate sensory projection: analytic structure and relevance to perception. Biological Cybernetics 25, pp. 181–194, 1977.
M. Tistarelli and G. Sandini. Estimation of depth from motion using an anthropomorphic visual sensor. Image and Vision Computing 8(4), pp. 271–278, 1990.
J.K. Tsotsos. Analyzing vision at the complexity level The Behavioral and Brain Sciences 13, pp. 423–469, 1990.
C.F.R. Weiman. Tracking algorithms using log-polar mapped image coordinates. Proc. SPIE Intelligent Robots and Computer Vision VIII: Algorithms and Techniques, pp. 843-853, Philadelphia (Pennsylvania) 1989.
A.L. Yarbus. “Eye movements and vision”, Plenum Press, 1967.
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1996 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Colombo, C., Rucci, M., Dario, P. (1996). Integrating Selective Attention and Space-Variant Sensing in Machine Vision. In: Sanz, J.L.C. (eds) Image Technology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-58288-2_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-58288-2_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-63528-1
Online ISBN: 978-3-642-58288-2
eBook Packages: Springer Book Archive