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People counting embedded in a camera

Start with the Function Pack

Making buildings and offices smarter means placing people at the heart of the environments we live and work in. This paradigm shift requires a particular attention by our surrounding electronics on the sensing intelligence. In this context, the people counting functionality becomes of paramount importance to adjust in real-time heater, HVAC or occupancy management. It results in more comfort for occupants and higher energy management efficiency.


– This prototype can count in real-time and with a high level of accuracy the restaurant’s attendance, while running on the standard STM32 microcontroller.
– This is achieved thanks to the artificial intelligence algorithm embedded on the STM32 microcontroller and the use of a thermal infrared technology.


Vision: Camera module bundle (reference: B-CAMS-OMV)


Data format:
Single class: people
RGB color images


Model: YOLO Low Complexity quantized neural network

Input size: 240x240x3

Memory footprint:
277 KB Flash for weights
233 KB RAM for activations

Accuracy: 55.88% Average Precision using a 50% IoU against the PASCAL VOC test dataset

Performance on STM32H747* (High-perf) @ 400 MHz 
Inference time: 371 ms
Frame rate: 2.7 fps

* As measured with STM32CubeAI 7.1.0 in FP-AI-VISION1 3.1.0