Quantitative Verification of Projected Views Using a Power Law Model of Feature Detection

We observe that conventional approaches to the construction of likelihood models of visual appearance for image features are non-quantitative, precluding their use in tasks such as hypothesis testing for projected view validation. This document outlines a quantitative approach for verification of 3D objects´ predicted edge features in images, which incorporates both the effects of image noise and local image structure. This approach supports the construction of a joint probability for the degree of conformity of image data to both edge orientation and location, without the need for arbitrary relative scale factors. The method has been validated on multiple views of man-made objects constructed froma variety of materials.