Model of frequency analysis in the visual cortex and the shape from texture problem

International Journal of Computer Vision

Volumn 76, Issue 2, 2008, Pages 165-182

  Massot, Corentin ^a   Hérault, Jeanny ^a  

^a GIPSA LAB   (France)

Author keywords

Biological model; Frequency estimation; Log normal filters; Model of V1; Shape from texture

Indexed keywords

ALGORITHMS; BIOACTIVITY; IMAGE PROCESSING; MATHEMATICAL MODELS; PROBLEM SOLVING;

SHAPE FROM TEXTURE;

FREQUENCY ESTIMATION;

EID: 38049127184     PISSN: 09205691     EISSN: 15731405     Source Type: Journal    
DOI: 10.1007/s11263-007-0048-x     Document Type: Article

References (40)

1. Atick, J., & Redlick, A. (1992). What does the retina know about natural scenes? Neural Computation, 4(2), 196-210.
2. Beaudot, W. H. (1994). The neural information in the vertebra retina: a melting pot of ideas for artificial vision. PhD thesis, Tirf laboratory, Grenoble, France.
3. Black, M. J., & Rosenholtz, R. (1995). Robust estimation of multiple surface shapes from occluded textures. In International symposium on computer vision (pp. 485-490), Miami, FL.
4. Carandini, M., Heeger, D. J., & Movshon, J. A. (1999). Linearity and gain control in v1 simple cells. In Cerebral cortex, Vol. XIII: Cortical models.
5. Carandini, M., Demb, J. B., Mante, V., Tolhurst, D. J., Dang, Y., Olshausen, B. A., Gallant, J. L. & Rust, N. C. (2005). Do we know what the early visual system does? Journal of Neuroscience, 25, 10577-10597.
6. Clerc, M., & Mallat, S. (2002). The texture gradient equation for recovering shape from texture. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(4), 536-549.
7. Daugman, J. G. (1980). Two-dimensional spectral analysis of cortical receptive field profiles. Vision Research, 20, 847-856.
8. DeValois, R. L. (1991). Orientation and spatial frequency selectivity: properties and modular organization. In A. Valberg & B. B. Lee (Eds.) From pigments to perception. New York: Plenum.
9. DeValois, R. L., Albrecht, D. G., & Thorell, L. G. (1982). Spatial frequency selectivity of cells in macaque visual cortex. Vision Research, 22, 545-559.
10. Field, D. J. (1987). Relations between the statistics of natural images and the response properties of cortical cells. Journal of the Optical Society of America A, 4, 2379-2394.
11. Fleming, R. W., Torralba, A., & Adelson, E. H. (2004). Specular reflections and the perception of shape. Journal of Vision, 4(9), 798-820.
12. Garding, J., & Lindeberg, T. (1996). Direct computation of shape cues using scale-adapted spatial derivative operators. International Journal of Computer Vision, 17(2), 163-191.
13. Gautama, T., & Van Hulle, M. M. (2003). Modeling motion processing in macaque area mt/v5: from single cells to population codes. In G.T. Buracas, O. Ruksenas, Geoffry M. Boynton, & T. Albright (Eds.), NATO science series (pp. 282-305). Amsterdam: IOS.
14. Gibson, J. J. (1950). The perception of the visual world. Boston: Houghton Mifflin.
15. Guerin-Dugue, A., & Elghadi, M. (1999). Shape from texture by local frequencies estimation. In SCIA (pp. 533-544), Kangerlussuaq, Greenland.
16. Heeger, D. J. (1993). Modeling simple-cell direction selectivity with normalized,half-squared, linear operators. Journal of Neurophysiology, 70, 1885-1898.
17. Hérault, J. (1996). A model of colour processing in the retina of vertebrates: from photoreceptors to colour opposition and colour constancy. Neurocomputing, 12, 113-129.
18. Hubel, D. H., & Wiesel, T. N. (1974). Sequence regularity and geometry of orientation columns in the monkey striate cortex. Journal of Computational Neurology, 158, 267-294.
19. Hwang, W. S., Lu, C. S., & Chung, P. C. (1998). Shape from texture estimation of planar surface orientation through the ridge surfaces of continuous wavelets transform. IEEE Transactions in Image Processing, 7(5), 773-780.
20. Jones, J., & Palmer, L. (1987). An evaluation of the two-dimensional gabor filter model of simple cell receptive fields in cat striate cortex. Journal of Neurophysiology, 58, 1233-1258.
21. Knill, D. C. (1998). Discriminating surface slant from texture: comparing human and ideal observers. Vision Research, 38(11), 1683-1711.
22. Knutsson, H., Westin, C. F., & Granlund, G. (1994). Local multiscale frequency and bandwidth estimation. In IEEE international conference on image processing (ICIP'94), Austin, TX.
23. Kovesi, P. (2003). Surface normals to surfaces via shapelets. In Proceedings of the Australia-Japan advanced workshop on computer vision, Adelaide. http://www.csse.uwa.edu.au/~pk/Research/MatlabFns/.
24. Landy, M. S., Maloney, L. T., Johnston, E. B., & Young, M. (1995). Measurement and modeling of depth cue combination: in defense of weak fusion. Vision Research, 35(3), 389-412.
25. Lazebnik, S., Schmid, C., & Ponce, J. (2005). A sparse texture representation using local affine regions. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(8), 1265-1278.
26. Lelandais, S., Boutté, L., & Plantier, J. (2005). Shape from texture: Local scales and vanishing line computation to improve results for macrotextures. International Journal of Image Graphics, 5(2), 329-350.
27. Li, A., & Zaidi, Q. (2004). Three-dimensional shape from non-homogeneous textures: carved and stretched surfaces. Journal of Vision, 4(10(3)), 860-878.
28. Lindeberg, T. (1998). Feature detection with automatic scale selection. International Journal of Computer Vision, 30(2), 77-116.
29. Liu, Y., Vogels, R., & Orban, G. A. (2004). Convergence of depth from texture and depth from disparity in macaque inferior temporal cortex. The Journal of Neuroscience, 24(15), 3795-3800.
30. Loh, A., & Kovesi, P. (2005). Shape from texture without estimating transformations. Technical report, UWA-CSSE-05-001, July 2005.
31. Malik, J., & Holtz, R. (1997). Computing local surface orientation and shape from texture for curved surfaces. International Journal of Computer Vision, 23(2), 149-168.
32. Qian, N. (1997). Binocular disparity and the perception of depth. Neuron, 18(3), 359-368.
33. Ribeiro, E., & Hancock, E. R. (2001). Shape from periodic texture using the eigenvectors of local affine distortion. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(12), 1459-1465.
34. Sakai, K., & Finkel, H. (1997). Spatial-frequency analysis in the perception of perspective depth. Network: Computation in Neural Systems, 8(3), 335-352.
35. Spillmann, L., & Werner, J. S. (1990). Visual perception: the neurophysiological foundations. New York: Academic Press.
36. Super, B. J., & Bovik, A. C. (1995). Shape from texture using local spectral moments. IEEE Transactions on Pattern Analysis and Machine Intelligence, 17(4), 333-343.
37. Super, B. J., & Bovik, A. C. (1995). Planar surface orientation from texture spatial frequencies. Pattern Recognition, 28(5), 728-743.
38. Torralba, A. B., & Hérault, J. (1999). An efficient neuromorphic analog network form motion estimation. IEEE Transactions on Circuits and Systems-I: Special Issue on Bio-Inspired Processors and CNNs for Vision, 46(2), 269-280.
39. Tsutsui, K. I., Sakata, H., Naganuma, T., & Taira, M. (2002). Neural correlates for perception of 3d surface orientation from texture gradient. Science, 298(5592), 409-412.
40. Wallis, G. (2001). Linear models of simple cells: correspondence to real cell responses and space spanning properties. Spatial Vision, 14(3-4), 237-260.