Classification of Thermal Images for Human-Machine Differentiation in Human-Robot Collaboration Using Convolutional Neural Networks
- Differentiation between human and non-human objects can increase efficiency of human-robot collaborative applications. This paper proposes to use convolutional neural networks for classifying objects in robotic applications. The body temperature of human beings is used to classify humans and to estimate the distance to the sensor. Using image classification with convolutional neural networks it isDifferentiation between human and non-human objects can increase efficiency of human-robot collaborative applications. This paper proposes to use convolutional neural networks for classifying objects in robotic applications. The body temperature of human beings is used to classify humans and to estimate the distance to the sensor. Using image classification with convolutional neural networks it is possible to detect humans in the surroundings of a robot up to five meters distance with low-cost and low-weight thermal cameras. Using transfer learning technique we trained the GoogLeNet and MobilenetV2. Results show accuracies of 99.48 % and 99.06 % respectively.…
Document Type: | Conference Proceeding |
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Conference Type: | Konferenzartikel |
Zitierlink: | https://opus.hs-offenburg.de/8394 | Bibliografische Angaben |
Title (English): | Classification of Thermal Images for Human-Machine Differentiation in Human-Robot Collaboration Using Convolutional Neural Networks |
Conference: | International Conference on Ubiquitous Robots (20. : 25-28 June 2023 : Honolulu, HI, USA) |
Author: | Urban HimmelsbachStaff MemberORCiD, Sinan SümeStaff Member, Thomas WendtStaff MemberORCiDGND |
Year of Publication: | 2023 |
Publisher: | IEEE |
First Page: | 730 |
Last Page: | 734 |
Parent Title (English): | 2023 20th International Conference on Ubiquitous Robots (UR) |
ISBN: | 979-8-3503-3517-0 (Elektronisch) |
ISBN: | 979-8-3503-3518-7 (Print on Demand) |
DOI: | https://doi.org/10.1109/UR57808.2023.10202384 |
Language: | English | Inhaltliche Informationen |
Institutes: | Fakultät Wirtschaft (W) |
Institutes: | Bibliografie |
Tag: | Cameras; Collaboration; Convolutional neural networks; Meters; Robot vision systems; Temperature sensors; Transfer learning | Formale Angaben |
Relevance: | Konferenzbeitrag: h5-Index < 30 |
Open Access: | Closed |
Licence (German): | Urheberrechtlich geschützt |