Dense matching quality evaluation - an empirical study

Z. Zhang, M. Gerke, M.S. Peter, M.Y. Yang, G. Vosselman

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

5 Citations (Scopus)
5 Downloads (Pure)

Abstract

The acquisition and processing techniques of Airborne Laser Scanning (ALS) data have improved rapidly in recent years. Due to the relative high costs of laser scanning, we want to explore the potential of detecting changes and updating Digital Surface Models using point clouds derived from Dense Image Matching (DIM). The prerequisite of this work is to evaluate dense matching quality. In this paper, a workflow is designed to evaluate dense matching quality using planar roof segments. ALS data are taken as reference. The workflow can be divided into two steps: roof detection and quality evaluation. Two types of accuracy plots are depicted based on single DIM points and single segments. The experimental results show the point-to-plane residuals of DIM points are around 3 cm.
Original languageEnglish
Title of host publicationProceedings of Joint urban remote sensing event (JURSE) 2017, 6-8 March 2017, Dubai, United Arab Emirates
Place of PublicationPiscataway
PublisherIEEE
Pages1-4
Number of pages4
ISBN (Electronic)978-1-5090-5808-2
DOIs
Publication statusPublished - 2017
EventJoint Urban Remote Sensing Event 2017 - Ritz-Carlton, Dubai, United Arab Emirates
Duration: 6 Mar 20178 Mar 2017
http://jurse2017.com/

Conference

ConferenceJoint Urban Remote Sensing Event 2017
Abbreviated titleJURSE 2017
Country/TerritoryUnited Arab Emirates
CityDubai
Period6/03/178/03/17
Internet address

Keywords

  • 2024 OA procedure

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