Cart (Loading....) | Create Account
Close category search window

3D object-based classification for vehicle extraction from airborne LiDAR data by combining point shape information with spatial edge

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Wei Yao ; Photogrammetry & Remote Sensing, Tech. Univ. Muenchen, Munich, Germany ; Hinz, S. ; Stilla, U.

The problem of vehicle extraction using airborne laser scanning (ALS) is studied under the framework of object-based point cloud analysis (OBPA). Object extraction relies on the partitioning of raw ALS data into various segments approximating semantic entities followed by classification. A 3D segmentation method working directly on point cloud is used, which features the detection of local arbitrary modes and the globally optimized organization of segments concurrently. To make the segmentation more competent in extracting small-scale objects such as vehicle, the detection of local structures is realized by adaptive mean shift (MS) using variable bandwidths which are determined by the point shape information bounded by spatial edge. The experimental results show that the proposed method performs very well in terms of visual interpretation as well as extraction accuracy.

Published in:

Pattern Recognition in Remote Sensing (PRRS), 2010 IAPR Workshop on

Date of Conference:

22-22 Aug. 2010

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.