Details
| Original language | English |
|---|---|
| Pages | 1-8 |
| Publication status | Published - 18 Oct 2015 |
| Event | 2015 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR) - West Lafayette, IN, USA, West Lafayette, United States Duration: 18 Oct 2015 → 20 Oct 2015 |
Conference
| Conference | 2015 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR) |
|---|---|
| Abbreviated title | SSRR |
| Country/Territory | United States |
| City | West Lafayette |
| Period | 18 Oct 2015 → 20 Oct 2015 |
Abstract
Autonomous mobile robots exploring areas in a search and rescue (SAR) context benefit greatly from the usage of thermal imaging cameras (TICs). In unknown environments, the interpretation of the temperature values provided by the camera is a challenge. This is due to the fact that temperature calculation based on thermal images depends strongly on the regarded surface emissivity. In this work, we show how to improve the temperature interpretation in thermal images making use of the diverse characteristics of the emissivity at varying viewing angles. Using several thermal images taken from different points of view, we are able to do a basic material classification. In combination with an algorithm that maps temperature values on the environment's 3D structure, we estimate the regarded surface emissivity and temperature. The presented approach is evaluated by a single camera setup using nonlinear optimization techniques.
ASJC Scopus subject areas
- Computer Science(all)
- Artificial Intelligence
- Engineering(all)
- Control and Systems Engineering
- Social Sciences(all)
- Safety Research
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2015. 1-8 Paper presented at 2015 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), West Lafayette, United States.
Research output: Contribution to conference › Paper › Research › peer review
}
TY - CONF
T1 - Improving the interpretation of thermal images with the aid of emissivity's angular dependency.
AU - Zeise, Björn
AU - Kleinschmidt, Sebastian P.
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: This work has partly been supported within H2020-ICT by the European Commission under grant agreement number 645101 (SmokeBot).
PY - 2015/10/18
Y1 - 2015/10/18
N2 - Autonomous mobile robots exploring areas in a search and rescue (SAR) context benefit greatly from the usage of thermal imaging cameras (TICs). In unknown environments, the interpretation of the temperature values provided by the camera is a challenge. This is due to the fact that temperature calculation based on thermal images depends strongly on the regarded surface emissivity. In this work, we show how to improve the temperature interpretation in thermal images making use of the diverse characteristics of the emissivity at varying viewing angles. Using several thermal images taken from different points of view, we are able to do a basic material classification. In combination with an algorithm that maps temperature values on the environment's 3D structure, we estimate the regarded surface emissivity and temperature. The presented approach is evaluated by a single camera setup using nonlinear optimization techniques.
AB - Autonomous mobile robots exploring areas in a search and rescue (SAR) context benefit greatly from the usage of thermal imaging cameras (TICs). In unknown environments, the interpretation of the temperature values provided by the camera is a challenge. This is due to the fact that temperature calculation based on thermal images depends strongly on the regarded surface emissivity. In this work, we show how to improve the temperature interpretation in thermal images making use of the diverse characteristics of the emissivity at varying viewing angles. Using several thermal images taken from different points of view, we are able to do a basic material classification. In combination with an algorithm that maps temperature values on the environment's 3D structure, we estimate the regarded surface emissivity and temperature. The presented approach is evaluated by a single camera setup using nonlinear optimization techniques.
UR - http://www.scopus.com/inward/record.url?scp=84967205658&partnerID=8YFLogxK
U2 - 10.1109/ssrr.2015.7442950
DO - 10.1109/ssrr.2015.7442950
M3 - Paper
SP - 1
EP - 8
T2 - 2015 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)
Y2 - 18 October 2015 through 20 October 2015
ER -