Retina-Like Sensors: Motivations, Technology and Applications

  • Giulio Sandini
  • Giorgio Metta


Retina-like visual sensors are characterized by space-variant resolution mimicking the distribution of photoreceptors of the human retina. These sensors, like our eyes, have a central part at highest possible resolution (called fovea) and a gradually decreasing resolution in the periphery. We will present a solid-state implementation of this concept. One attractive property of space-variant imaging is that it allows processing the whole image at frame rate while maintaining the same field of view of traditional rectangular sensors. The resolution is always maximal if the cameras are allowed to move and the fovea placed over the regions of interest. This is the case in robots with moving cameras. As an example of possible applications, we shall describe a robotic visual system exploiting two retina-like cameras and using vision to learn sensorimotor behaviors.


Visual Sensor Image Transmission Binocular Disparity Robot Head CMOS Implementation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Baron T, Levine MD, Hayward V, Bolduc M, Grant DA (1995) A biologically-motivated robot eye system. Paper presented at the 8th Canadian Aeronautics and Space Institute (CASI) Conference on Astronautics, Ottawa, CanadaGoogle Scholar
  2. Baron T, Levine MD, Yeshurun Y (1994) Exploring with a foveated robot eye system. Paper presented at the 12th International Conference on Pattern Recognition, Jerusalem, IsraelGoogle Scholar
  3. Blough PM (1979) Functional implications of the pigeon’s peculiar retinal structure. Granda AM, Maxwell JM (eds) Neural Mechanisms of Be havior in the Pigeon (pp. 71–88). Plenum Press, New York, NYGoogle Scholar
  4. Capurro C, Panerai F, Sandini G (1997) Dynamic vergence using log-polar images. Int J Comput Vision 24: 79–94CrossRefGoogle Scholar
  5. Carpenter RHS (1988) Movements of the Eyes (Second ed.). Pion Limited, LondonGoogle Scholar
  6. Darrell T, Gordon G, Harville M, Woodall J (2000) Integrated person tracking using stereo, color, and pattern detection. Int J Comput Vision 37: 175–185CrossRefGoogle Scholar
  7. Engel G, Greve DN, Lubin JM, Schwartz EL (1994) Space-variant active vision and visually guided robotics: design and construction of a high-performance miniature vehicle. Paper presented at the International Conference on Pattern Recognition, JerusalemGoogle Scholar
  8. Galifret Y (1968) Les diverses aires fonctionelles de la retine du pigeon. Z Zellforsch 86: 535–545PubMedCrossRefGoogle Scholar
  9. Koenderink J, Van Doom J (1991) Affine structure from motion. J Optical Soc Am 8: 377–385CrossRefGoogle Scholar
  10. Manzotti R, Gasteratos A, Metta G, Sandini G (2001) Disparity estimation in log polar images and vergence control. Comput Vis Image Und 83: 97–117CrossRefGoogle Scholar
  11. Metta G (2000) Babybot: a study on sensori-motor development. Unpublished Ph.D. Thesis, University of Genova, GenovaGoogle Scholar
  12. Metta G, Sandini G, Konczak J (1999) A developmental approach to visually-guided reaching in artificial systems. Neural Networks 12: 1413–1427PubMedCrossRefGoogle Scholar
  13. Metta G, Carlevarino A, Martinotti R, Sandini G (2000) An incremental growing neural network and its application to robot control. Paper presented at the International Joint Conference on Neural Networks, Como, ItalyGoogle Scholar
  14. Natale L, Metta G, Sandini G (2002) Development of auditory-evoked reflexes: visuo-acoustic cues integration in a binocular head. Robot Auton Syst 39: 87–106CrossRefGoogle Scholar
  15. Panerai F, Metta G, Sandini G (2000) Visuoinertial stabilization in space-variant binocular systems. Robot Auton Syst 30: 195–214CrossRefGoogle Scholar
  16. Panerai F, Metta G, Sandini G (2002) Learning stabilization reflexes in robots with moving eyes. Neurocomputing 48: 323–337CrossRefGoogle Scholar
  17. Rojer A, Schwartz EL (1990) Design considerations for a space-variant visual sensor with complex-logarithmic geometry. Paper presented at the 10th International Conference on Pattern Recognition, Atlantic City, USAGoogle Scholar
  18. Sandini G (1997) Artificial systems and neuroscience. Paper presented at the Otto and Martha Fischbeck Seminar on Active Vision, Berlin, GermanyGoogle Scholar
  19. Sandini G, Tagliasco V (1980) An anthropomorphic retina-like structure for scene analysis. Comp Vision Graph 14: 365–372Google Scholar
  20. Schwartz EL (1980) A quantitative model of the functional architecture of human striate cortex with application to visual illusion and cortical texture analysis. Biol Cybern 37: 63–76PubMedCrossRefGoogle Scholar
  21. Srinivasan MV, Venkatesh S (eds) (1997) From Living Eyes to Seeing Machines. Oxford University Press, LondonGoogle Scholar
  22. Tunley H, Young D (1994) First order optical flow from log-polar sampled images. Paper presented at the Third European Conference on Computer Vision, StockholmGoogle Scholar
  23. Van der Spiegel J, Kreider G, Claeys C, Debusschere I, Sandini G, Dario P, Fantini F, Bellutti P, Soncini G (1989) A foveated retina-like sensor using CCD technology. In: Mead C, Ismail M (eds), Analog VLSI Implementation of Neural Systems (pp. 189–212). Kluwer Acad Publ, BostonCrossRefGoogle Scholar
  24. Wallace RS, Ong PW, Bederson BB, Schwartz EL (1994) Space variant image processing. Int J Comput Vision 13: 71–91CrossRefGoogle Scholar
  25. Weiman CFR (1988) 3-D Sensing with polar exponential sensor arrays. Paper presented at the SPIE - Digital and Optical Shape Representation and Pattern RecognitionGoogle Scholar
  26. Weiman CFR, Chaikin G (1979) Logarithmic spiral grids for image processing and display. Computer Graphic and Image Processing 11: 197–226CrossRefGoogle Scholar
  27. Weiman CFR, Juday RD (1990) Tracking algorithms using log-polar mapped image coordinates. Paper presented at the SPIE International Conference on Intelligent Robots and Computer Vision VIII: Algorithms and Techniques, Philadelphia (PA)Google Scholar

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© Springer-Verlag Wien 2003

Authors and Affiliations

  • Giulio Sandini
  • Giorgio Metta

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