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3.3: Questions

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    Chapter 3 Questions

    1. Differentiate between passive and active sensors.

    2. What is the energy in a photon?

    3. How are chemo-reception and photo-reception similar?

    4. Describe the three most significant imperfections in biological vision systems and what causes them.

    5. Discuss the relationship between connectivity and spatial and temporal acuity

    6. What is coarse coding?

    7. What are the three information domains in which vision systems extract environmental information?

    8. Describe the three major compound eye designs.

    9. Give some examples of visual scanning systems in the animal kingdom. What are the advantages and disadvantages of such a system?

    10. Why is the retina considered a part of the brain, since the two organs are separated by distance and other components (optic nerve, LGN, etc.)?

    11. What are the anatomical similarities between the retina, LGN, and the brain?

    12. Explain the serial/planar duality that exists in biological vision systems.

    13. Describe the encoding and decoding levels (in orders of magnitude) in the various organs within the primate vision system.

    14. Name the five major cell types (layers) in the retina. Which three are connected to the triad synapse?

    15 Give the three primary vision information channels in primate vision.

    16. DoG or LoG filters are primarily used to model what part of the vision system?

    17. What are the commonalities in color vision models concerning luminance and color?

    18. What is the photoreceptor mosaic, and how is that like an artistic mosaic?

    19. What is the difference between LoG and DoG filters?

    20. Discuss degrees of freedom with LoG and DoG filters?

    21. Compare and contrast vision system pathways with a conventional wavelet filter bank.

    22. How is coarse coding manifested in the vision system?

    23. When contemplating a new communication encoding scheme, it is very important to choose an orthogonal basis. But a typical biological set of basis functions are not mutually orthogonal. What is the implication?

    24. Why are we so interested in biology if natural basis functions are not orthogonal?

    Chapter 3 References:

    [Boyn60] Boynton, R., “Theory of Color Vision”, Journal of the OSA, Vol. 50, No. 10, pp. 929–944, 1960.

    [Brooks18] Brooks, G., “Gaussian-based filters for elementary motion detector delay element: Modeling spatio-temporal pathways with elementary motion detection”, IEEE Research and Applications of Photonics in Defense, Shalimar, Florida, 2018.

    [Chittka96] Chittka, L., “Optimal sets of color receptors and opponent processing for coding of natural objects in insect vision”, Journal of Theoretical Biology, Vol. 181, pp. 179–196, 1996.

    [Daug88] Daugman, J., “Complete discrete 2-D Gabor transforms by neural networks for image analysis and compression”, IEEE Trans. On Acoustic, Speech, and Signal Processing, Vol. 36, No. 7, 1988.

    [Del94] Delbruck, T. and Mead, C., “Analog VLSI adaptive, logarithmic, wide-dynamic-range photoreceptor”, IEEE Int. Symp. Circuits Syst, pp. 339–342, 1994.

    [DeV88] DeValois, R. and DeValois, K., Spatial Vision, Oxford University Press, New York, 1988.

    [DeV96] DeValois, R. and DeValois, K., “On ‘A three-stage color model’ ”, Vision Research, Vol. 36, No. 6, pp. 833–836, 1996.

    [Dowl87] Dowling, J. E., The Retina: An Approachable Part of the Brain, Harvard University Press, Cambridge, Massachusetts, 1987.

    [Dup18] Dubeyroux, J., et al., M2APix: a bio-inspired auto-adaptive visual sensor for robust ground height estimation, IEEE, ISBN: 978-1-5386-4881-0, 2018.

    [Giak18] Giakos, G., et al., “Integration of Bioinspired Vision Principles Towards the Design of Autonomous Guidance, Navigation, and Control Systems”, 9th Int. Conf. on Information, Intelligence, Systems and App. (IISA), pp. 1–8, DOI: 10.1109/IISA.2018.8633643, 2018.

    [Guth91] Guth, L. S., “Model for color vision and light adaptation”, Journal of the Optical Society of America, Vol. 8, No. 6, 1991.

    [Guth96] Guth, L. S., “Comments on ‘A multi-stage color model’ ”, Vision Research, Vol. 36, No. 6, pp. 831–833, 1996.

    [Hass56] Hassenstein, B. and Reichardt, W., “Systemtheoretische Analyse der Zeit-, Reihenfolgen und Vorzeichenauswertung bei der Bewegungsperzeption des Russelkafers Chlorophanus”, Zeitsschrift fur Naturforschung, Teil B, Vol. 11, pp. 513–524, 1956.

    [Lee18] Lee, S., et al., “Foveated retinal optimization for see-through near-eye multi-layer displays”, IEEE Access, DOI: 10.1109/ACCESS.2017.2782219, Feb. 14, 2018.

    [Liu15a] Chapter 3, “Silicon Retinas”, in Liu, S., et al., Event-based Neuromorphic Systems, John Wiley & Sons, ISBN: 978-0470018491, 2015.

    [Liu15b] Chapter 4, “Silicon Cochleas”, in Liu, S., et al., Event-based Neuromorphic Systems, John Wiley & Sons, ISBN: 978-0470018491, 2015.

    [Lyon89] Lyon, R. and Mead, C., Ch 16 “Electronic Cochlea”, in Mead, C, Ed., Analog VLSI and Neural Systems, Addison-Wesley, ISBN: 0-201-05992-4, 1989.

    [Maf15] Mafrica, S., et al., “A bio-inspired analog silicon retina with Michaelis-Menten auto-adaptive pixels sensitive to small and large changes in light”, Optics Express, Vol. 23, No. 5, p. 5614, 2015.

    [Maha89] Mahawald, M. and Mead, C., Ch 15 “Silicon Retina”, in Mead, C, Ed., Analog VLSI and Neural Systems, Addison-Wesley, ISBN: 0-201-05992-4, 1989.

    [Maha91] Mahawald, M., “Silicon retinal with adaptive photoreceptors”, SPIE Visual Information Processing: From Neurons to Chips, Vol. 1473, No. 4, Orlando, April 1991.

    [Marr82] Marr, D., Vision, W. H. Freeman and Company, New York, 1982.

    [Mart94] Martinez-Uriegas, E., “Chromatic-achromatic multiplexing in human color vision”, in Kelly, D., Ed., Visual Science and Engineering: Models and Applications, Marcel Dekker, Inc., 1994.

    [Rob20] Robertson, J., et al., “Toward neuromorphic photonic networks of ultrafast spiking neurons”, IEEE Journal of Selected Topics in Quantum Electronics, Vol. 26, No. 1, 2020.

    [Roub12] Roubieu, F. L., Serres, J., Franceschini, N., Ruffier, F., and Viollet, S., “A fully-autonomous hovercraft inspired by bees: Wall following and speed control in straight and tapered corridors”, 2012 IEEE International Conference on Robotics and Biomimetics (ROBIO), Guangzhou, 2012, pp. 1311–1318, DOI: 10.1109/ROBIO.2012.6491150.

    [Smith00] Smith, C. U. M., Biology of Sensory Systems, John Wiley, and Sons, ISBN: 0-471-85461-1, 2000.

    [Srini02] Srinivasan, M. V., “Visual Flight Control and Navigation in Honeybees: Applications to Robotics,” in Ayers, Davis, and Rudolph, Eds., Neurotechnology for Biomimetic Robots, MIT Press, Cambridge, Massachusetts, 2002.

    [Srini11] Srinivasan, M. V., “Honeybees as a model for the study of visually guided flight, navigation, and biologically inspired robotics,” Physiological Reviews, Vol. 91, No. 2, pp. 413–460, 2011.

    [Strang96] Strang, G. and Nguyen, T., Wavelets and Filter Banks, Wellesley-Cambridge Press, ISBN: 0-9614088-7-1, 1996.

    [Van17] Vanhoutte, E., et al. “A Quasi-Panoramic Bio-inspired Eye for Flying Parallel to Walls”, IEEE Sensors, doi: 10.1109/icsens.2017.8234110, 2017.

    [Werb91] Werblin, F. and Teeters, J., “Real-time simulation of the retina allowing visualization of each processing stage”, Proceedings of the SPIE, Vol. 1472, 1991.

    [WikiMM] Wikipedia, “Michaelis–Menten kinetics”, Oct. 2020.

    [Wu12] Wu, H., et al., “Insect-inspired high-speed motion vision system for robot control”, Biological Cybernetics, Vol. 106, pp. 453–463, DOI: 10.1007/s00422-012-0509-3, 2012.

    [Zag04] Zaghloul, K. and Boahen, K., “Optic nerve signals in a neuromorphic chip I: Outer and inner retina models”, IEEE Trans. Biomed. Eng., Vol. 51, No. 4, pp. 657–666, 2004.

    This page titled 3.3: Questions is shared under a CC BY-NC-SA 4.0 license and was authored, remixed, and/or curated by Geoffrey Brooks (Florida State Open Publishing) via source content that was edited to the style and standards of the LibreTexts platform; a detailed edit history is available upon request.