6. Specular Planar Target Surface Recovery via Coded Target Stereopsis

A key challenge facing computer vision systems is the presence of highly specular surfaces. Such surfaces present a challenge to conventional vision systems due to their reflective nature, which can mask the true structure of the surface and lead to incorrect measurements when traditional computer vision algorithms are used. Here we present a novel approach to reconstructing the local surface structure of highly specular, planar objects. The local surface structure of an object is obtained by utilizing the specular nature of the surface directly, rather than by making the common assumption that specularities are rare or do not exist. The basis of the technique presented here is to project controlled light patterns onto the object’s surface and to infer local surface structure by examining the interaction of the illuminant and the surface. The approach can be used to recover both specular and diffuse surface regions. Experimental results demonstrate the effectiveness of the approach.