Crafting the right synthetic data to train top-performing in-cabin monitoring systems
DMS, OMS, HMI… We are heading 2022 and there is no doubt that interior sensing applications are rising exponentially, and they will continue to do so in the coming months.
Why does developing accurate in-cabin monitoring systems require specific data generation technology?
Privacy issues and children rights, inaccurate data, lack of variability… There are important barriers developers need to overcome in order to train their deep learning models and real-world data is not always an option.
About the speaker:
Javier Salado is Technical Product Manager at Anyverse. He has over 30 years of experience in software development and systems integration, highlighting his time at HP and more recently at Samsung Research where he applied his experience in deep learning-related projects. He is Anyverse's product technical expert and point of contact for applications such as sensor simulation or deep learning training using advanced hyperspectral synthetic data.
With Anyverse™ you can accurately simulate any camera sensor and help you decide which one will perform better with your perception system. No more complex and expensive experiments with real devices, thanks to our state-of-the-art photometric pipeline.
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