Research output per year
Research output per year
Neelu Madan, Mia Sandra Nicole Siemon, Magnus Kaufmann Gjerde, Bastian Starup Petersson, Arijus Grotuzas, Malthe Aaholm Esbensen, Ivan Adriyanov Nikolov, Mark Philip Philipsen, Kamal Nasrollahi, Thomas B. Moeslund
Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review
In this paper, we propose ThermalSynth, a novel approach for creating synthetic thermal images by mixing 3D characters generated using the Unity game engine with real thermal backgrounds. We use a shader based on the Stefan-Boltzmann law [18] to approximate the appearance in the thermal domain of the synthetic characters. Additionally, we provide a post-processing pipeline to better blend the high-fidelity synthetic data with the lower-resolution real thermal surveillance one. The proposed approach is used to create a dataset for people falling into water near a harbor front. Diverse scenarios of such falls are generated with an ample amount of data to enable the use of deep learning algorithms. To demonstrate the effectiveness of the generated data, we train two standard deep neural networks (AlexNet and ResNet-18) on our synthetic thermal dataset using a supervised learning approach. We test our system on small datasets containing real video footage of actual falls. We observe that training these simple classification networks yields an accuracy of 98.70% at a sensitivity of 100% on the real-world voluntary fall dataset. The code for Ther-malSynth and the dataset is publically available at https://github.com/NeeluMadan/Thermal-Synth.
Original language | English |
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Title of host publication | Proceedings - 2023 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, WACVW 2023 |
Number of pages | 10 |
Publisher | IEEE (Institute of Electrical and Electronics Engineers) |
Publication date | 5 Jan 2023 |
Pages | 130-139 |
ISBN (Print) | 979-8-3503-2057-2 |
ISBN (Electronic) | 979-8-3503-2056-5 |
DOIs | |
Publication status | Published - 5 Jan 2023 |
Event | 2023 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, WACVW 2023 - Waikoloa, United States Duration: 3 Jan 2023 → 7 Jan 2023 |
Conference | 2023 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, WACVW 2023 |
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Country/Territory | United States |
City | Waikoloa |
Period | 03/01/2023 → 07/01/2023 |
Series | IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW) |
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ISSN | 2572-4398 |
Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review