Methods for LiDAR point cloud classification using local neighborhood statistics

Angela M. Kim; Richard C. Olsen; Fred A. Kruse

doi:10.1117/12.2015709

20 May 2013 Methods for LiDAR point cloud classification using local neighborhood statistics

Angela M. Kim, Richard C. Olsen, Fred A. Kruse

Proceedings Volume 8731, Laser Radar Technology and Applications XVIII; 873103 (2013) https://doi.org/10.1117/12.2015709
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

Abstract

LiDAR data are available in a variety of publicly-accessible forums, providing high-resolution, accurate 3- dimensional information about objects at the Earth's surface. Automatic extraction of information from LiDAR point clouds, however, remains a challenging problem. The focus of this research is to develop methods for point cloud classification and object detection which can be customized for specific applications. The methods presented rely on analysis of statistics of local neighborhoods of LiDAR points. A multi-dimensional vector composed of these statistics can be classified using traditional data classification routines. Local neighborhood statistics are defined, and examples are given of the methods for specific applications such as building extraction and vegetation classification. Results indicate the feasibility of the local neighborhood statistics approach and provide a framework for the design of customized classification or object detection routines for LiDAR point clouds.

Citation Download Citation

Angela M. Kim, Richard C. Olsen, and Fred A. Kruse "Methods for LiDAR point cloud classification using local neighborhood statistics", Proc. SPIE 8731, Laser Radar Technology and Applications XVIII, 873103 (20 May 2013); https://doi.org/10.1117/12.2015709

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available