TY - GEN
T1 - Compact covariance descriptors in 3D point clouds for object recognition
AU - Fehr, Duc
AU - Cherian, Anoop
AU - Sivalingam, Ravishankar
AU - Nickolay, Sam
AU - Morellas And, Vassilios
AU - Papanikolopoulos, Nikolaos
PY - 2012
Y1 - 2012
N2 - One of the most important tasks for mobile robots is to sense their environment. Further tasks might include the recognition of objects in the surrounding environment. Three dimensional range finders have become the sensors of choice for mapping the environment of a robot. Recognizing objects in point clouds provided by such sensors is a difficult task. The main contribution of this paper is the introduction of a new covariance based point cloud descriptor for such object recognition. Covariance based descriptors have been very successful in image processing. One of the main advantages of these descriptors is their relatively small size. The comparisons between different covariance matrices can also be made very efficient. Experiments with real world and synthetic data will show the superior performance of the covariance descriptors on point clouds compared to state-of-the-art methods.
AB - One of the most important tasks for mobile robots is to sense their environment. Further tasks might include the recognition of objects in the surrounding environment. Three dimensional range finders have become the sensors of choice for mapping the environment of a robot. Recognizing objects in point clouds provided by such sensors is a difficult task. The main contribution of this paper is the introduction of a new covariance based point cloud descriptor for such object recognition. Covariance based descriptors have been very successful in image processing. One of the main advantages of these descriptors is their relatively small size. The comparisons between different covariance matrices can also be made very efficient. Experiments with real world and synthetic data will show the superior performance of the covariance descriptors on point clouds compared to state-of-the-art methods.
UR - http://www.scopus.com/inward/record.url?scp=84864440731&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84864440731&partnerID=8YFLogxK
U2 - 10.1109/ICRA.2012.6224740
DO - 10.1109/ICRA.2012.6224740
M3 - Conference contribution
AN - SCOPUS:84864440731
SN - 9781467314039
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 1793
EP - 1798
BT - 2012 IEEE International Conference on Robotics and Automation, ICRA 2012
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2012 IEEE International Conference on Robotics and Automation, ICRA 2012
Y2 - 14 May 2012 through 18 May 2012
ER -