In Search of Inliers: 3D Correspondence by Local and Global Voting

Anders Glent Buch, Yang Yang, Norbert Kruger, Henrik Gordon Petersen; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014, pp. 2067-2074

Abstract


We present a method for finding correspondence between 3D models. From an initial set of feature correspondences, our method uses a fast voting scheme to separate the inliers from the outliers. The novelty of our method lies in the use of a combination of local and global constraints to determine if a vote should be cast. On a local scale, we use simple, low-level geometric invariants. On a global scale, we apply covariant constraints for finding compatible correspondences. We guide the sampling for collecting voters by downward dependencies on previous voting stages. All of this together results in an accurate matching procedure. We evaluate our algorithm by controlled and comparative testing on different datasets, giving superior performance compared to state of the art methods. In a final experiment, we apply our method for 3D object detection, showing potential use of our method within higher-level vision.

Related Material


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[bibtex]
@InProceedings{Buch_2014_CVPR,
author = {Glent Buch, Anders and Yang, Yang and Kruger, Norbert and Gordon Petersen, Henrik},
title = {In Search of Inliers: 3D Correspondence by Local and Global Voting},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2014}
}