In this article we will try to answer several questions: why is the near infrared band key for (camera-based) in-cabin monitoring systems to perform well in low light? Why is simulating the NIR a challenge? What solutions have been used so far to simulate it? How does Anyverse simulate it?
Tag Archives: Interior sensing
Synthetic data to train and validate in-cabin monitoring systems
Why should you seriously consider synthetic data to train and validate in-cabin monitoring systems? What are the advantages of synthetic data versus real-world data to train these systems? And why are many DMS/OMS developers already implementing synthetic data in their data generation pipelines?
In-cabin monitoring use cases and data needs
There are several in-cabin monitoring use cases, and likewise, they have different data needs, hence, different data challenges that you need to overcome if you want to successfully train the deep learning models behind the systems.
Acquiring data to develop in-cabin monitoring systems – The challenges
Whether it’s DMS, OMS, or any other interior camera system, acquiring data to develop in-cabin monitoring systems is challenging. But… Why is that? Why is acquiring real-world data particularly hard for the in-cabin monitoring use case?