Dense matching quality evaluation - an empirical study

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

doi:10.1109/JURSE.2017.7924579

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 proceeding › Chapter › Academic › peer-review

5 Citations (Scopus)

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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 language	English
Title of host publication	Proceedings of Joint urban remote sensing event (JURSE) 2017, 6-8 March 2017, Dubai, United Arab Emirates
Place of Publication	Piscataway
Publisher	IEEE
Pages	1-4
Number of pages	4
ISBN (Electronic)	978-1-5090-5808-2
DOIs	https://doi.org/10.1109/JURSE.2017.7924579
Publication status	Published - 2017
Event	Joint Urban Remote Sensing Event 2017 - Ritz-Carlton, Dubai, United Arab Emirates Duration: 6 Mar 2017 → 8 Mar 2017 http://jurse2017.com/

Conference

Conference	Joint Urban Remote Sensing Event 2017
Abbreviated title	JURSE 2017
Country/Territory	United Arab Emirates
City	Dubai
Period	6/03/17 → 8/03/17
Internet address	http://jurse2017.com/

Keywords

2024 OA procedure

Access to Document

10.1109/JURSE.2017.7924579

ArticleFinal published version, 2.91 MBLicence: Taverne

Cite this

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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.",

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Zhang, Z, Gerke, M, Peter, MS, Yang, MY & Vosselman, G 2017, Dense matching quality evaluation - an empirical study. in Proceedings of Joint urban remote sensing event (JURSE) 2017, 6-8 March 2017, Dubai, United Arab Emirates. IEEE, Piscataway, pp. 1-4, Joint Urban Remote Sensing Event 2017, Dubai, United Arab Emirates, 6/03/17. https://doi.org/10.1109/JURSE.2017.7924579

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PY - 2017

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Dense matching quality evaluation - an empirical study

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