Industrial technology company FLIR Systems has announced the creation of the FLIR Thermal Imaging Regional Dataset program for machine learning advanced driver assistance development (ADAS) and autonomous vehicle (AV) systems.
Specific to major cities, FLIR has also announced San Francisco as the first available dataset, enabling developers to evolve convolutional neural networks with FLIR’s Autonomous Developer Kit (ADK), a cost-effective, weatherproof thermal camera developed for ADAS and AV testing.
Building on a free dataset program that FLIR launched in 2018 of more than 14,000 annotated thermal images of day and night scenes, the San Francisco thermal dataset features nearly 10,000 annotated thermal images with 181,000 annotations in thermal and the corresponding visible camera images. It includes new variations in weather including fog and rain plus additional driving scenes at different hours of the day.
With the introduction of city-specific datasets, FLIR also increased the number of annotation classes to include car, sign, light, people, truck, bus, hydrant, bike, rider, motorcycle, and train.
Frank Pennisi, President of the Industrial Business Unit at FLIR said, ‘Creating datasets takes time and resources, and the datasets FLIR has created empowers the automotive community to more quickly evaluate thermal sensors on next-generation algorithms.’
‘When combined with visible light cameras in an Automatic Emergency Braking (AEB) system, the thermal data will create a more comprehensive, redundant, and safer system in cars today,’ added Pennisi.