Tobii at InCabin Sensing Berlin

In the beginning of 2024, we announced our acquisition of DTS AutoSense from Xperi Inc. Tobii now offers both driver and occupant monitoring centric solutions, with the commitment to change the interior sensing market.

Event details

Join us at InCabin.sensing Berlin to meet the Tobii Autosense team! Learn more about our offerings designed to create a safer, more intuitive, and comfortable in-cabin experience for everyone in the car.

No matter if your challenge is to meet regulation, or implement features that offer unique, more comfortable, and intuitive in-cabin experiences. Our team would love to learn about your needs and discuss how we can support you.

Visit us at booth #21.

Discover our leading solutions for OMS and DMS

In the Tobii Autosense demo car — a BMW X5 — you can explore our interior sensing solutions:

• NFoV safety-centric solution: (DMS)
• WFvO rearview mirror single-camera solution that combines safety with experience (DMS+OMS)

Book a meeting with us to secure a seat in the demo car!

Eye tracking glasses for UX design and HMI 

Our experts will also showcase Tobii Pro Glasses 3, our eye tracking glasses that offer UX / HMI professionals the ability to improve UX design by capturing the behavior of individuals’ eyes in real-life scenarios. 

Speaker session at InCabin Sensing

Beyond the beep: Unveiling the algorithmic challenges of Driver Monitoring Systems

Speaker: Anders Wirkestrand, Director of Product Management at Tobii

Description: Driver monitoring systems (DMS) hold promise for improving road safety by detecting driver drowsiness and distraction. But what if these systems fall short? How do limitations in the algorithm’s capabilities to provide signals that are both robust and accurate affect the system’s ability to enhance traffic safety?

This talk will delve into the shortcomings of existing driver monitoring systems and dive deep into key algorithm approaches used for extracting key signals like gaze and eye openness. We’ll discuss how the choice between these algorithms may significantly impact the rate of incorrect or missed distraction and drowsiness warnings.