Stereo Integration, Mean Field Theory and Psychophysics

Abslracl. We dcscribe a thcorctical formulation for stereo in terms of the Bayesian approach to vision and rclatc it to psychophysical experiments. The formulation enables us to integrate the depth information from dilI'erent types of matching primitives, or from different vision modules. Wc solvc the correspondence problem using comparibiliry constraints bctwecn fcatures and prior assumprions on the interpolared surfaces that result from the marching. We use techniques from sraristical physics to show how our theory relates lo previous work. Finally we show that, by a suilable choice of prior assumptions about surfaces, the theory is consisrent with some psychophysical experiments which investigate the rclarive importance of different marching primitives.