Skip to main content
SpringerLink
Log in

Motion Detection and Digital Polarization

  • Chapter
A Biologically Inspired CMOS Image Sensor

Part of the book series: Studies in Computational Intelligence ((SCI,volume 461))

  • 2108 Accesses

Abstract

Flying insects have extraordinary visual capabilities. Their ability to detect fast motion in the visual scene and avoid collision using low level image processing and little computational power makes their visual processing interesting for real time motion/collision detection in machine vision applications.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Adelson, E., Bergen, J.: The plenoptic function and the elements of early vision. In: Landy, M., Movshon, J. (eds.) Computational Models of Visual Processing, pp. 3–20. MIT Press, Cambridge (1991)

    Google Scholar 

  2. Barron, J., Fleet, D., Beauchemin, S.: Systems and experiment performance of optical flow techniques. International Journal of Computer Vision 12(1), 43–77 (1994)

    Article  Google Scholar 

  3. Negahdaripour, S., Horn, B.: Direct passive navigation. IEEE Transactions on Pattern Analysis and Machine Intelligence 9(1), 168–176 (1987)

    Article  MATH  Google Scholar 

  4. Anderson, C., Burt, P., van der Wal, G.: Change detection and tracking using pyramid transformation techniques. In: Proceedings of SPIE-Intelligent Robotics and Computer Vision, vol. 579, pp. 72–78 (1985)

    Google Scholar 

  5. Haritaoglu, I., Davis, L., Harwood, D.: W4 who? when? where? what? a real time system for detecting and tracking people. In: International Conference on Automatic Face and Gesture Recognition, pp. 222–227 (1998)

    Google Scholar 

  6. Wren, C., Azarbayejani, A., Darrell, T., Pentland, A.: Pfinder: Real-time tracking of the human body. IEEE Transactions on Pattern Analysis and Machine Intelligence 19(7), 780–785 (1997)

    Article  Google Scholar 

  7. Doretto, G., Soatto, S.: Editable dynamic textures. In: IEEE Proceedings of Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 137–142 (2003)

    Google Scholar 

  8. Elgammal, A., Harwood, D., Davis, L.: Non-parametric Model for Background Subtraction. In: Vernon, D. (ed.) ECCV 2000. LNCS, vol. 1843, pp. 751–767. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  9. Borst, A.: How do flies land? from behavior to neuronal circuits. Bio-Science 40(4), 292–299 (1990)

    Google Scholar 

  10. Brinkworth, R., O’Carroll, D.: Robust models for optic codeing in natural scences inspired by insect biology. PLoS Computational Biology 5(11), 1–14 (2009)

    Article  Google Scholar 

  11. Tanner, J., Mead, C.: An integrated analog optical motion sensor. In: VLSI Signal Processing II, pp. 59–76. IEEE Press, New York (1986)

    Google Scholar 

  12. Delbrück, T.: Silicon retina with correlation-based, velocity-tuned pixels. IEEE Transactions on Neural Networks 4(3), 529–541 (1993)

    Article  Google Scholar 

  13. Kramer, J.: Compact integrated motion sensor with three-pixel interaction. IEEE Transactions on Pattern Analysis and Machine Intelligence 18(4), 455–460 (1996)

    Article  Google Scholar 

  14. Moini, A., Bouzerdoum, A., Eshraghian, K., Yakovleff, A., Nguyen, X., Blanksby, A., Beare, R., Abbott, D., Bogner, R.: An insect vision based motion detection chip. IEEE Journal of Solid-State Circuits 32(2), 279–283 (1997)

    Article  Google Scholar 

  15. Collins, R.T., Lipton, A.J., Kanade, T., Fujiyoshi, H., Duggins, D., Tsin, Y., Tolliver, D., Enomoto, N., Hasegawa, O., Burt, P., Wixson, L.: A system for video surveillance and monitoring. CMU VSAM Final Report, 1–69 (1999)

    Google Scholar 

  16. Lichtsteiner, P., Posch, C., Delbrück, T.: A A 128×128 120db 30mw asynchronous vision sensor that responds to relative intensity change. In: IEEE ISSCC Digest of Technical Papers, pp. 508–509 (2006)

    Google Scholar 

  17. Innocent, M., Meynants, G.: Differential image senor with high common mode rejection. In: Proceedings of European Solid-State Circuits Conference, pp. 483–486 (2005)

    Google Scholar 

  18. Shafie, S., Kawahito, S., Halin, I., Hasan, W.: Non-linearity in wider dynamic range CMOS image sensors utilizing a partial charge transfer technique. Sensors 9, 9452–9467 (2009)

    Article  Google Scholar 

  19. Srinivasan, M.V., Zhang, S.W., Chahl, J.S., Barth, E., Venkatesh, S.: How honeybees make grazing landings on flat surfaces. Biological Cybernetics 83, 171–183 (2000)

    Article  Google Scholar 

  20. Borst, A.: Correlation versus gradient type motion detectors: the pros and cons. Philosophical Transactions of the Royal Society, B: Biological Sciences 362(1479), 369–374 (2007)

    Article  Google Scholar 

  21. Reichardt, W.: Autocorrelation, a principle for the evaluation of sensory information by the central nervous system. Principles of Sensory Communication, 303–317 (1961)

    Google Scholar 

  22. Okuno, H., Yagi, T.: Bio-inspired real-time robot vision for collision avoidance. Journal of Robotics and Mechatronics 20(1), 68–74 (2008)

    Google Scholar 

  23. Harrison, R.: A biologically inspired analog IC for visual collision detection. IEEE Transactions on Circuits and Systems-I 52(11), 2308–2318 (2005)

    Article  Google Scholar 

  24. Reiser, M., Dickinson, M.: A test bed for insect-inspired robotic control. Philosophical Transactions of the Royal Society, A: Mathematical, Physical and Engineering Sciences 361, 2267–2285 (2003)

    Article  MathSciNet  Google Scholar 

  25. Neumann, T.R., Bülthoff, H.H.: Behavior-oriented vision for biomimetic flight control. In: Proceedings of the International Workshop on Biologically Inspired Robotics, pp. 196–203 (2002)

    Google Scholar 

  26. Krapp, H.: Neuronal matched filters for optic flow processing in flying insects. In: Neurological Processing of Optic Flow, pp. 93–120. Academic Press, San Diego (2000)

    Google Scholar 

  27. Tao, S., Zeng, L.: An elementary-motion-detector based on hardware lateral inhibition network. Journal of Physics: Conference Series 48, 212–216 (2006)

    Article  Google Scholar 

  28. Lee, D.: A theory of visual control of braking based on information about time-to-collision. Perception 5, 437–459 (1976)

    Article  Google Scholar 

  29. Horn, B., Schunck, P.: Determining optical flow. Artificial Intelligence 17, 185–203 (1981)

    Article  Google Scholar 

  30. Decker, S., McGrath, R., Brehmer, K., Sodini, C.: A 256 x 256 CMOS imaging array with wide dynamic range pixels and column- parallel digital output. IEEE Journal of Solid-State Circuits 33, 2081–2091 (1998)

    Article  Google Scholar 

  31. Akahane, N., Sugawa, S., Adachi, S., Mori, K., Ishiuchi, T., Mizobuchi, K.: A sensitivity and linearity improvement of a 100db dynamic range CMOS image sensor using a lateral overflow integration capacitor. In: Symposium on VLSI Circuits, Digest of Technical Papers, pp. 62–65 (2005)

    Google Scholar 

  32. Yadid-Pecht, O., Fossum, E.: Wide intrascene dynamic range cmos aps using dual sampling. IEEE Transactions on Electron Devices 44, 1721–1723 (1997)

    Article  Google Scholar 

  33. Yang, D., Gamal, A.E., Fowler, B., Tian, H.: A 640 x 512 cmos image sensor with ultra-wide dynamic range floating-point pixel level ADC. IEEE Journal of Solid-State Circuits 34, 1821–1834 (1999)

    Article  Google Scholar 

  34. Buchner, E.: Elementary movement detectors in an insect visual system. Biological Cybernetics 24, 85–101 (1976)

    Article  Google Scholar 

  35. van Hateren, J., Snippe, H.P.: Information theoretical evaluation of parametric models of gain control in blowfly photoreceptor cells. Vision Research 41(14), 1851–1865 (2001)

    Article  Google Scholar 

  36. Buchner, E.: Behavioural analysis of spatial vision in insects. In: Photoreception and Vision in Invertebrates. A: Life Sciences, New York, London, vol. 74, pp. 561–621 (1984)

    Google Scholar 

  37. Borst, A., Egelhaaf, M.: Principles of visual motion detection. Trends in Neurosciences 12(8), 297–306 (1989)

    Article  Google Scholar 

  38. Sarkar, M., Segundo, D.S., van Hoof, C., Theuwissen, A.: An analog and digital representation of polarization using CMOS image sensor. In: Proceedings of 5th European Optical Society Tropical Meeting on Advanced Imaging Techniques (2010) ISBN: 9783000305030

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Electrical Engineering Dept, Indian Institute of Technology Delhi, Hauz Khas, 110016, New Delhi, India

    Mukul Sarkar

  2. Harvest Imaging , Kleine Schoolstraat 9, 3960, Bree, Belgium

    Albert Theuwissen

Authors
  1. Mukul Sarkar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Albert Theuwissen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mukul Sarkar .

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Sarkar, M., Theuwissen, A. (2013). Motion Detection and Digital Polarization. In: A Biologically Inspired CMOS Image Sensor. Studies in Computational Intelligence, vol 461. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34901-0_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-34901-0_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34900-3

  • Online ISBN: 978-3-642-34901-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation