TY - GEN
T1 - DPN-LRF
T2 - 11th International Symposium on Advances in Visual Computing, ISVC 2015
AU - Akizuki, Shuichi
AU - Hashimoto, Manabu
PY - 2015
Y1 - 2015
N2 - For the purpose of 3D keypoint matching, a Local Reference Frame (LRF), a local coordinate system of the keypoint, is one important information source for achieving repeatable feature descriptions and accurate pose estimations. We propose a robust LRF for two main point cloud disturbances: density differences and partial occlusions. To generate LRFs that are robust to such disturbances, we employ two strategies: normalizing the effects of point cloud density by approximating the surface area in the local region and using the dominant orientation of a normal vector around the keypoint. Experiments confirm that the proposed method has higher repeatability than state-of-the-art methods with respect to density differences and partial occlusions. It was also confirmed that the method enhances the reliability of keypoint matching.
AB - For the purpose of 3D keypoint matching, a Local Reference Frame (LRF), a local coordinate system of the keypoint, is one important information source for achieving repeatable feature descriptions and accurate pose estimations. We propose a robust LRF for two main point cloud disturbances: density differences and partial occlusions. To generate LRFs that are robust to such disturbances, we employ two strategies: normalizing the effects of point cloud density by approximating the surface area in the local region and using the dominant orientation of a normal vector around the keypoint. Experiments confirm that the proposed method has higher repeatability than state-of-the-art methods with respect to density differences and partial occlusions. It was also confirmed that the method enhances the reliability of keypoint matching.
UR - http://www.scopus.com/inward/record.url?scp=84952663015&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84952663015&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-27857-5_78
DO - 10.1007/978-3-319-27857-5_78
M3 - Conference contribution
AN - SCOPUS:84952663015
SN - 9783319278568
VL - 9474
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 878
EP - 887
BT - Advances in Visual Computing - 11th International Symposium, ISVC 2015, Proceedings
PB - Springer Verlag
Y2 - 14 December 2015 through 16 December 2015
ER -