Charles F. Chubb

Research Interests

Somehow, instant by instant, human vision converts the stream of 2-dimensional images stimulating the retina into the full-blown 3-dimensional world, populated by objects in space, that is given to us prior to any conscious effort. My research aims to understand this computational miracle from several angles. First, I use neural networks to study how vision tunes itself to detect the characteristic structures in its environment. This research takes a wide-angle perspective on the genesis of vision, and of perceptual systems in general. By contrast, another branch of my work uses psychophysical methods to study human visual processing from the bottom up.

When we think of visual sensors, we think first of retinal receptors (rods and cones). Increasingly, however, we are realizing the importance of supraretinal sensor classes; for instance, neural arrays for sensing motion, stereo disparity, texture.

Such sensor classes define the kinds of elementary stuff that exist for vision. I use histogram contrast analysis, a new branch of psychophysical theory that I have developed over the past years, to (i) isolate individual, supraretinal visual sensor classes, and (ii) measure what each class senses. The ultimate goal of this work is to construct a table of elementary types of visual stuff analogous to the periodic table of physical elements.

Selected Publications

Chubb, C. and Sperling, G. (1988). Drift-balanced random stimuli: a general basis for studying non-Fourier motion perception. Journal of the Optical Society of America A 5, 1986-2007.

Chubb, C., Sperling, G. and Solomon, J. (1989). Texture interactions determine perceived contrast. Proceedings of the National Academy of Sciences USA 86, 9631-9635.

Chubb, C. and Sperling, G. (1991). Texture quilts: basic tools for studying motion from texture. Journal of Mathematical Psychology 35, 411-442.

Solomon, J.A., Sperling, G. and Chubb, C. (1993). The lateral inhibition of perceived contrast is indifferent to on-center/off-center segregation, but specific to orientation. Vision Research 33, 2671-2683.

Chubb, C., Econopouly, J. and Landy, M.S. (1994). Histogram contrast analysis and the visual segregation of IID textures. Journal of the Optical Society of America A 11, 2350-2374.

C. Chubb, J-L. Lu & G. Sperling, Structure detection: a statistically certified unsupervised learning procedure," Vision Research, In press, 1997.

Department of Cognitive Sciences Faculty

Department of Cognitive Sciences

UC Irvine Vision Group

Institute for Mathematical Behavioral Sciences

UC Irvine School of Social Sciences