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Front-end computations in human vision

This document explores the front-end computations underlying human vision, focusing on models and representations utilized in visual processing. Highlighting key references from experts like DeValois, Hubel, and Malik, it discusses the structure of monocular and binocular visual fields, cone and rod functions, and modeling simple cells through Gaussian derivatives. It also emphasizes the significance of orientation energy in visual perception, detailing methodologies such as K-means clustering of filter responses and the mapping from retina to cortical areas, enriching our understanding of vision complexities.

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Front-end computations in human vision

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  1. Front-end computations in human vision Jitendra Malik U.C. Berkeley References: DeValois & DeValois,Hubel, Palmer, Spillman &Werner, Wandell

  2. Cerebral Cortex

  3. Monocular Visual Field: 160 deg (w) X 135 deg (h)Binocular Visual Field: 200 deg (w) X 135 deg (h)

  4. Cones and Rods

  5. ON and OFF cells in retinal ganglia

  6. Modeling simple cells • Elongated directional Gaussian derivatives • 2nd derivative and Hilbert transform • L1 normalized for scale invariance • 6 orientations, 3 scales • Zero mean

  7. Orientation Energy • Gaussian 2nd derivative and its Hilbert pair • Can detect combination of bar and edge features; also insensitive to linear shading [Perona&Malik 90] • Multiple scales

  8. Visual Processing Areas

  9. Macaque Visual Areas

  10. Textons (Malik et al, IJCV 2001) • K-means on vectors of filter responses

  11. Textons (cont.)

  12. Texton Histograms Chi square test: i 0.1 j k 0.8

  13. CSF as function of eccentricity

  14. Receptor density vs eccentricity

  15. Cortical Magnification Factor

  16. Mapping from Retina to V1

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