Model-based object recognition using the Hausdorff distance with explicit pairing

In this paper, we consider the problem of recognizing 3D object from a single 2D intensity image obtained from unknown position and orientation. We propose the feature set based correspondence algorithm between 3-D model features and 2-D image features, in contrast to the conventional approaches which use a single local feature or fixed number of local features. As a measure of the similarity between feature sets, the Hausdorff distance with explicit paring (HDEP) is proposed and extended to the partial HDEP, using the notion of the partial distance to cope with the problems which occur when there are backgrounds and some of image features are missing or severely deviated from each original value. The 3D object recognition system using this algorithm with hypothesis-verification scheme is implemented and tested on real images with backgrounds and occlusion.