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Comprehensive Utilization of Temporal and Spatial Domain Outlier Detection Methods for Mobile Terrestrial LiDAR Data
Department of Earth and Space Science, York University, 4700 Keele Street, Toronto, ON M3J 1P3, Canada
Industrial and 3D Imaging Department, Optech Incorporated, 300 Interchange Way, Vaughan, ON L4K 5Z8, Canada
* Author to whom correspondence should be addressed.
Received: 25 June 2011; in revised form: 29 July 2011 / Accepted: 8 August 2011 / Published: 16 August 2011
Abstract: Terrestrial LiDAR provides many disciplines with an effective and efficient means of producing realistic three-dimensional models of real world objects. With the advent of mobile terrestrial LiDAR, this ability has been expanded to include the rapid collection of three-dimensional models of large urban scenes. For all its usefulness, it does have drawbacks. One of the major problems faced by the LiDAR industry today is the automatic removal of outlying data points from LiDAR point clouds. This paper discusses the development and combined implementation of two methods of performing outlier detection in georeferenced point clouds. These methods made use of the raw data available from most time-of-flight mobile terrestrial LiDAR scanners in both the temporal and spatial domains. The first method involved a moving fixed interval smoother derived from the well-known position velocity acceleration Kalman Filter. The second method fitted a quadratic curved surface to sections of LiDAR data. The combined use of these routines is discussed through examples with real LiDAR data.
Keywords: outlier detection; mobile terrestrial LiDAR; curved surface fitting; Kalman Filter
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Cite This Article
MDPI and ACS Style
Leslar, M.; Wang, J.-G.; Hu, B. Comprehensive Utilization of Temporal and Spatial Domain Outlier Detection Methods for Mobile Terrestrial LiDAR Data. Remote Sens. 2011, 3, 1724-1742.
Leslar M, Wang J-G, Hu B. Comprehensive Utilization of Temporal and Spatial Domain Outlier Detection Methods for Mobile Terrestrial LiDAR Data. Remote Sensing. 2011; 3(8):1724-1742.
Leslar, Michael; Wang, Jian-guo; Hu, Baoxin. 2011. "Comprehensive Utilization of Temporal and Spatial Domain Outlier Detection Methods for Mobile Terrestrial LiDAR Data." Remote Sens. 3, no. 8: 1724-1742.