TY - GEN
T1 - Comparison of surface normal estimation methodsfor range sensing applications
AU - Klasing, Klaas
AU - Althoff, Daniel
AU - Wollherr, Dirk
AU - Buss, Martin
PY - 2009
Y1 - 2009
N2 - As mobile robotics is gradually moving towards a, level of semantic environment understanding, robust 3D object, recognition plays an increasingly important role. One of the, most crucial prerequisites for object recognition is a set of fast, algorithms for geometry segmentation and extraction, which in, turn rely on surface normal vectors as a fundamental feature., Although there exists a plethora of different approaches for, estimating normal vectors from 3D point clouds, it is largely, unclear which methods are preferable for online processing on, a mobile robot. This paper presents a detailed analysis and, comparison of existing methods for surface normal estimation, with a special emphasis on the trade-off between quality and, speed. The study sheds light on the computational complexity, as well as the qualitative differences between methods and, provides guidelines on choosing the 'right' algorithm for the, robotics practitioner. The robustness of the methods with re-, spect to noise and neighborhood size is analyzed. All algorithms, are benchmarked with simulated as well as real 3D laser data, obtained from a mobile robot.
AB - As mobile robotics is gradually moving towards a, level of semantic environment understanding, robust 3D object, recognition plays an increasingly important role. One of the, most crucial prerequisites for object recognition is a set of fast, algorithms for geometry segmentation and extraction, which in, turn rely on surface normal vectors as a fundamental feature., Although there exists a plethora of different approaches for, estimating normal vectors from 3D point clouds, it is largely, unclear which methods are preferable for online processing on, a mobile robot. This paper presents a detailed analysis and, comparison of existing methods for surface normal estimation, with a special emphasis on the trade-off between quality and, speed. The study sheds light on the computational complexity, as well as the qualitative differences between methods and, provides guidelines on choosing the 'right' algorithm for the, robotics practitioner. The robustness of the methods with re-, spect to noise and neighborhood size is analyzed. All algorithms, are benchmarked with simulated as well as real 3D laser data, obtained from a mobile robot.
UR - http://www.scopus.com/inward/record.url?scp=70350367567&partnerID=8YFLogxK
U2 - 10.1109/ROBOT.2009.5152493
DO - 10.1109/ROBOT.2009.5152493
M3 - Conference contribution
AN - SCOPUS:70350367567
SN - 9781424427895
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 3206
EP - 3211
BT - 2009 IEEE International Conference on Robotics and Automation, ICRA '09
T2 - 2009 IEEE International Conference on Robotics and Automation, ICRA '09
Y2 - 12 May 2009 through 17 May 2009
ER -