Recognition of 3D package shapes for single camera metrology

Abstract

Many applications of 3D object measurement have become commercially viable due to the recent availability of low-cost range cameras such as the Microsoft Kinect. We address the application of measuring an object's dimensions for the purpose of billing in shipping transactions, where high accuracy is required for certification. In particular, we address cases where an object's pose reduces the accuracy with which we can estimate dimensions from a single camera. Because the class of object shapes is limited in the shipping domain, we perform a closed-world recognition in order to determine a shape model which can account for missing parts, and/or to induce the user to reposition the object for higher accuracy. Our experiments demonstrate that the addition of this recognition step significantly improves system accuracy.