Recovery of surface pose from texture orientation statistics under perspective projection
In a seminal paper, Witkin (1981) derived a model of surface slant and tilt recovery based on the statistics of the orientations of texture elements (texels) on a planar surface. This model made use of basic mathematical properties of probability distributions to formulate a posterior distribution on slant and tilt given a set of image orientations under orthographic projection. One problem with the Witkin model was that it produced a posterior distribution with multiple maxima, reflecting the inherent ambiguity in scene reconstruction under orthographic projection. In the present article, we extend Witkin's method to incorporate the effects of perspective projection. An identical approach is used to that of Witkin; however, the model now reflects the effects of perspective projection on texel orientation. Performance of the new model is compared against that of Witkin's model in a basic surface pose recovery task using both a maximum a posteriori (MAP) decision rule and a rule based on the expected value of the posterior distribution. The resultant posterior of the new model is shown to have only one maximum and thereby the ambiguity in scene interpretation is resolved. Furthermore, the model performs better than Witkin's model using both MAP and expected value decision rules. The results are discussed in the context of human slant estimation.
shape from texture computational vision human vision