Details
| Originalsprache | Englisch |
|---|---|
| Seiten | 88-95 |
| Seitenumfang | 8 |
| Publikationsstatus | Veröffentlicht - 26 Okt. 2017 |
| Veranstaltung | 2017 IEEE International Symposium on Safety, Securtiy and Rescue Robotics (SSRR) - Shanghai, China, Shanghai, China Dauer: 11 Okt. 2017 → 13 Okt. 2017 |
Konferenz
| Konferenz | 2017 IEEE International Symposium on Safety, Securtiy and Rescue Robotics (SSRR) |
|---|---|
| Kurztitel | SSRR |
| Land/Gebiet | China |
| Ort | Shanghai |
| Zeitraum | 11 Okt. 2017 → 13 Okt. 2017 |
Abstract
Although the generation of 3D temperature maps has become a frequently used technique, not only in search and rescue applications but also during inspection tasks, the remote measurement of a surface's true temperature is still a huge challenge. In this work, we face the problem of creating corrected 3D temperature maps in unknown environments without prior knowledge of surface emissivities. Using a calibrated sensor stack consisting of a 3D laser range finder and a thermal imaging camera, we generate Tempered Point Clouds (TPCs). With the help of the TPCs, we show how to perform a basic material classification, i.e. to make a distinction between metal and dielectric surface areas. For this purpose, we investigate measurements taken from different viewing angles. With the help of this approach, it is also possible to estimate corrected surface temperatures. The presented methods are evaluated making use of the OctoMap framework.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Artificial intelligence
- Ingenieurwesen (insg.)
- Sicherheit, Risiko, Zuverlässigkeit und Qualität
- Mathematik (insg.)
- Steuerung und Optimierung
- Sozialwissenschaften (insg.)
- Sicherheitsforschung
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- BibTex
- RIS
2017. 88-95 Beitrag in 2017 IEEE International Symposium on Safety, Securtiy and Rescue Robotics (SSRR), Shanghai, China.
Publikation: Konferenzbeitrag › Paper › Forschung › Peer-Review
}
TY - CONF
T1 - Tempered point clouds and octomaps - A step towards true 3D temperature measurement in unknown environments.
AU - Zeise, Björn
AU - Wagner, Bernardo
N1 - DBLP's bibliographic metadata records provided through http://dblp.org/search/publ/api are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions. Funding Information: ACKNOWLEDGMENT This work has partly been supported within H2020-ICT by the European Commission under grant agreement number 645101 (SmokeBot).
PY - 2017/10/26
Y1 - 2017/10/26
N2 - Although the generation of 3D temperature maps has become a frequently used technique, not only in search and rescue applications but also during inspection tasks, the remote measurement of a surface's true temperature is still a huge challenge. In this work, we face the problem of creating corrected 3D temperature maps in unknown environments without prior knowledge of surface emissivities. Using a calibrated sensor stack consisting of a 3D laser range finder and a thermal imaging camera, we generate Tempered Point Clouds (TPCs). With the help of the TPCs, we show how to perform a basic material classification, i.e. to make a distinction between metal and dielectric surface areas. For this purpose, we investigate measurements taken from different viewing angles. With the help of this approach, it is also possible to estimate corrected surface temperatures. The presented methods are evaluated making use of the OctoMap framework.
AB - Although the generation of 3D temperature maps has become a frequently used technique, not only in search and rescue applications but also during inspection tasks, the remote measurement of a surface's true temperature is still a huge challenge. In this work, we face the problem of creating corrected 3D temperature maps in unknown environments without prior knowledge of surface emissivities. Using a calibrated sensor stack consisting of a 3D laser range finder and a thermal imaging camera, we generate Tempered Point Clouds (TPCs). With the help of the TPCs, we show how to perform a basic material classification, i.e. to make a distinction between metal and dielectric surface areas. For this purpose, we investigate measurements taken from different viewing angles. With the help of this approach, it is also possible to estimate corrected surface temperatures. The presented methods are evaluated making use of the OctoMap framework.
UR - http://www.scopus.com/inward/record.url?scp=85040228846&partnerID=8YFLogxK
U2 - 10.1109/ssrr.2017.8088145
DO - 10.1109/ssrr.2017.8088145
M3 - Paper
SP - 88
EP - 95
T2 - 2017 IEEE International Symposium on Safety, Securtiy and Rescue Robotics (SSRR)
Y2 - 11 October 2017 through 13 October 2017
ER -