Why is simulating the near infrared key for in-cabin sensing?

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?

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?

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?

How to train an accurate and reliable in-cabin monitoring system

The automotive interior sensing market was demanding a specific technology capable of successfully covering (in a cost & time-efficient manner) a wide range of potential issues when developing interior monitoring systems. Anyverse™ has responded and has brought a specific solution for interior simulation based on its top-performing synthetic data generation platform.

Client Story

Would you like to know how Cron AI has improved LiDAR simulation accuracy with physically correct synthetic data?

Let's talk about synthetic data!

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