Peer-Reviewed Journal Details
Mandatory Fields
Corcoran, P;Winstanley, A;Mooney, P;Middleton, R
2011
December
IEEE Transactions on Intelligent Transportation Systems
Background Foreground Segmentation for SLAM
Published
4 ()
Optional Fields
SIMULTANEOUS LOCALIZATION TRACKING
12
1177
1183
To perform simultaneous localization and mapping (SLAM) in dynamic environments, static background objects must first be determined. This condition can be achieved using a priori information in the form of a map of background objects. Such an approach exhibits a causality dilemma, because such a priori information is the ultimate goal of SLAM. In this paper, we propose a background foreground segmentation method that overcomes this issue. Localization is achieved using a robust iterative closest point implementation and vehicle odometry. Background objects are modeled as objects that are consistently located at a given spatial location. To improve robustness, classification is performed at the object level through the integration of a new segmentation method that is robust to partial object occlusion.
PISCATAWAY
1524-9050
10.1109/TITS.2011.2143706
Grant Details