Visual perception is fundamentally
ambiguous
because any single retinal image is consistent with an infinite number
of three-dimensional scenes. With the help of Bayesian modelling,
we are
interested
in unravelling the prior constraints used by the human visual system to
disambiguate the retinal images. Examples of prior constraints
under
study include the assumptions that the light source is located
above the
observer and that the observer's viewpoint is located above the
attended object.
Collaborators:
Further
references:
Kersten, D.,
Mamassian, P. & Yuille, A. (2004). Object perception as
Bayesian inference. Annual
Review of Psychology, 55, 271-304.
Mamassian, P. & Landy, M. S. (1998). Observer biases in the 3D interpretation of line drawings. Vision Research, 38, 2817-2832.
Mamassian, P. & Landy, M. S. (2001). Interaction of visual prior constraints. Vision Research, 41, 2653-2668.
Mamassian, P.,
Landy, M. S. &
Maloney, L. T. (2002). Bayesian
Modelling of Visual Perception. In R. Rao, B. Olshausen and M.
Lewicki (Eds.) Probabilistic Models of the Brain: Perception and
Neural Function (pp. 13-36). Cambridge, MA: MIT Press.
Notes on the
figure: