Official websites use. Share sensitive information only on official, secure websites. Thermopile sensor arrays provide a sufficient counterbalance between person detection and localization while preserving privacy through low resolution.
The latter is especially important in the context of smart building automation applications. The drawbacks in precision due to the sparse amount of labeled data were counteracted with a novel generative image generator IIG. This generator creates synthetic thermal frames from the sparse amount of available labeled data. Multiple robustness tests were performed during the evaluation process to determine the overall usability of the aforementioned algorithms as well as the advantage of the image generator.
They also prove to be robust against disturbances of warm air streams, sun radiation, the replacement of the sensor with an equal type sensor, new persons, cold objects, movements along the image frame border and people standing still. However, the precision decreases for persons wearing thick layers of clothes, such as winter clothing, or in scenarios where the number of present persons exceeds the number of persons the algorithm was trained on.
In summary, both algorithms are suitable for detection and localization purposes, although YOLOv5m has the advantage in real-time image processing capabilities, accompanied by a smaller model size and slightly higher precision. Keywords: people localization, thermopile array, multi-person detection, infrared array sensor, generative IR data. The presence detection of a person with and without movement is essential within many aspects of building automation, such as smart lighting systems [ 1 ], elderly fall detection [ 2 , 3 , 4 ] or movement tracking [ 5 , 6 ].
Based on the difference in two time-consecutive images, properties like the number of occupants or their direction of movement can be detected and localized [ 5 , 8 , 9 ].
