Heterogeneous feature based correspondence estimation

Abstract

This paper gives an insight in the preliminary results of an ongoing work about heterogeneous point feature estimation acquired from different type of sensors including structured light camera, stereo camera and a custom 3D laser range finder. The main goal of the paper is to compare the performance of the different type of local descriptors for indoor office environment. Several type of 3D features were evaluated on different datasets including the output of an enhanced stereo image processing algorithm too. From the extracted features the correspondences were determined between two different recording positions for each type of sensor. These correspondences were filtered and the final benchmarking of the extracted feature correspondences were compared for the different data sets. Further on, there is proposed an open access dataset for public evaluation of the proposed algorithms.