Lowering the barriers of entry for thermal-camera adoption
To enable ADAS developers to rapidly integrate and understand the benefits of thermal cameras in rounding out their sensor suite, FLIR’s team within the OEM division recently released a free machine-learning starter thermal dataset (click here). The dataset features a compilation of more than 14,000 annotated thermal images of people, cars, other vehicles, bicycles, and dogs in day and nighttime environments, enabling developers to begin testing and evolving convolutional neural networks (CNNs). By utilizing the dataset, they can quickly see the comprehensive and redundant system benefits of thermal detection (Fig. 6).
With its unique capabilities to improve safety for vehicles with automation levels from 1 to 5, plus a clear path forward for mass adoption, it’s a matter of when, not if, thermal cameras become an integral part of the ADAS and AV ecosystem.
About the author:
Paul Clayton is Vice President & General Manager, OEM and Emerging Markets Segment, FLIR Systems Inc. - www.flir.com
This article was first published in Electronic Design - www.electronicdesign.com