tinyML Summit 2021 tiny Talks: Person Detection under Extreme Constraints: Lessons from the Field



tinyML Summit 2021 https://www.tinyml.org/event/summit-2021
tiny Talks
“Person Detection under Extreme Constraints: Lessons from the Field”
Koen HELWEGEN, Deep Learning Scientist, Plumerai

We present various computer vision applications on microcontrollers that are enabled by Binarized Neural Networks (BNNs). This includes state-of-the-art models on the Arm Cortex-M4 architecture for the Visual Wake Words benchmark task (84.5% accuracy with under 170ms latency on a STM32F407VG) and person detection with bounding boxes. Moving beyond artificial benchmarks, we demonstrate the performance in real-world settings by deploying on an off-the-shelf Arm Cortex-M4 microcontroller with an inexpensive, low-power OV2680 camera. These applications are built using our integrated stack for training and inference of BNNs as well as through the collection, labeling and monitoring of custom designed datasets for TinyML. This combination results in highly-accurate and highly-efficient BNN models for cheap, low-power microcontrollers. We discuss practical tips for developing demanding computer vision applications on microcontrollers and highlight some of the lessons we learnt while developing BNNs for the real-world, such as our emphasis on high-quality, richly annotated data and powerful, hardware-based neural architecture search.

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