Thermal Imaging Dataset for Person Detection
| Autor: | Mate Krišto, Marina Ivašić-Kos |
|---|---|
| Přispěvatelé: | Biljanović, Petar (ur.). |
| Rok vydání: | 2019 |
| Předmět: |
010302 applied physics
business.product_category Biometrics Person detection thermal imaging surveillance access control dataset biometric Computer science Image quality business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Training (meteorology) 02 engineering and technology Telephoto lens 01 natural sciences law.invention Set (abstract data type) Lens (optics) law 0103 physical sciences Thermal 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence business Level of detail |
| Zdroj: | MIPRO |
| DOI: | 10.23919/mipro.2019.8757208 |
| Popis: | In this paper will be presented an original thermal dataset designed for training machine learning models for person detection. The dataset contains 7412 thermal images of humans captured in various scenarios while walking, running, or sneaking. The recordings are captured in the LWIR segment of the electromagnetic (EM) in various weather condition- clear, fog and rain at different distances from the camera, different body positions (upright, hunched) and movement speeds (regular walking, running). In addition to the standard lens of the camera, we used a telephoto lens for video recording, and we compared the image quality at different weather conditions and at different distances in both cases and set parameters that provided the level of detail in the image that can be used to detect the person. |
| Databáze: | OpenAIRE |
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