Recognition of 3D package shapes for single camera metrology

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.