Determining Three-Dimensional Shape from Orientation and Spatial Frequency Disparities

Binocular diierences in orientation and foreshortening are systematically related to surface slant and tilt and could potentially be exploited by biological and machine vision systems. Indeed, human stereopsis may possess a mechanism that speciically makes use of these orientation and spatial frequency disparities, in addition to the usual cue of horizontal disparity. In machine vision algorithms, orientation and spatial frequency disparities are a source of error in nding stereo correspondence because one seeks to nd features or areas which are similar in the two views when, in fact, they are systematically diierent. In other words, it is common to treat as noise what is useful signal. We have been developing a new stereo algorithm based on the outputs of linear spatial lters at a range of orientations and scales. We present a method in this framework, making use of orientation and spatial frequency disparities, to directly recover local surface slant. An implementation of this method has been tested on curved surfaces and quantitative experiments show that accurate surface orientation can be recovered eeciently. This method does not require the explicit identiication of oriented line elements and also provides an explanation of the intriguing perception of surface slant in the presence of orientation or spatial frequency disparities, but in the absence of systematic positional correspondence.