Evaluation kit leverages AI software and CMOS image sensor for driver and passenger monitoring

OmniVision Technologies, Inc. has partnered with in-cabin driver monitoring software company Jungo Connectivity to create an evaluation kit for driver and passenger monitoring that utilizes artificial intelligencesoftware and a CMOS image sensor designed specifically for driver monitoring.

Designed to enable original equipment manufacturers (OEM) and Tier-1 automotive designers to develop the next generation of driver and occupant monitoring systems for advanced driver assistance systems (ADAS), semi-autonomous vehicles, and fully-autonomous vehicles, the kit combines Jungo’s CoDriver software development kit (SDK) with OmniVision’s OV2311 CMOS image sensor, which is built on OmniPixel3-GS global shutter technology. CoDriver is a camera-based driver monitoring software solution that is based on deep learning, machine learning, and computer vision algorithms. The software provides the car with a complete, real-time picture of the driver’s condition, and together with additional ADAS components through sensor fusion, helps cars better understand the relationships between events, both internal and external to the vehicle cabin, according to Jungo.

Designed for mainstream driver monitoring applications, the OV2311 is a black and white 2 MPixel CMOS image sensor with a 3 µm pixel size that can capture high-quality video up to 60 fps in a 1600 x 1300 resolution format, which is designed to fit the driver's head box to ensure reliable monitoring regardless of driver height or seat position. It is reportedly adept at offering exceptionally accurate gaze- and eye-tracking capabilities and comes in a 7.2 x 6.2 mm automotive chip-scale package (a-CSP), which allows it to be discreetly designed into the cockpit of the vehicle. The sensor supports a 4-lane MIPI and 12-bit double-data-rate digital video port (DVP) interface.

OmniVision notes that, according to the National Highway Traffic Safety Administration, 80% of car accidents are caused by distracted driving. This evaluation kit was designed to obtain the "the most complete, real-time picture of the driver’s condition—regardless of the lighting conditions." It will also be able to accurately determine whether the driver is ready to take control in a semi-autonomous emergency scenario. If not, according to the company, the vehicle can take an alternative action, such as pulling off the road and parking. Additionally, in a fully autonomous experience, the sensors and software provide reliable information about the passengers’ characteristics, possessions, and emotional and medical states, not only of the driver, but also of passengers as far back as the third row.

"Increasingly advanced capabilities are necessary to enable safer and more intelligent automotive systems that will power not only next-generation ADAS, but also the first fully autonomous vehicles," said Cliff Cheng, senior director of automotive marketing at OmniVision. "For all of these next-generation occupant monitoring and identification applications, the ability to perform optimally in low- or no-light conditions is a must. OmniVision and Jungo’s combined solution provides customers such high performing, time-to-market solution."

Version 1.5 of Jungo’s SDK is included in the kit, which has been configured and tested to perform optimally with the OV2311 image sensor, in real time and using a live video stream. The kit is available now.

View more information on OmniVision.
View more information on Jungo.

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