Seeing Machines, a global leader in vision-based safety technology, recently announced the successful debut of its next-generation 3D Cabin Perception Mapping platform at CES 2026, marking a significant step forward in real-time in-cabin monitoring intelligence for future mobility.
While exterior perception mapping in automated driving focuses on a multi-sensor reconstruction of the vehicle’s surrounding environment, the Seeing Machines 3D perception mapping solution demonstrated live at CES delivers a comprehensive, real-time digital reconstruction of inside the vehicle cabin, enabling a holistic, accurate and scalable approach to interior sensing. Built on a “clean-sheet” architecture, the platform is designed to support multiple cameras, multiple occupants and a wide range of features, all from a single, high-trust perception layer.
Unlike traditional feature-by-feature approaches, Seeing Machines’ 3D Cabin Perception Mapping solves for the entire cabin simultaneously, improving consistency across features and maintaining accuracy even in the presence of intermittent or noisy sensor data.
The architecture provides a powerful abstraction layer that decouples feature development from underlying camera configurations and raw sensing implementations. This allows features to be built once and deployed seamlessly across multiple product configurations, reducing development effort, cost and time to market.
“This is a fundamental shift in how interior sensing systems are designed and deployed and the feedback from our CES engagements has been overwhelmingly positive,” said John Noble, Chief Technology Officer at Seeing Machines. “By moving from feature-specific pipelines to a unified 3D perception of the cabin, we enable higher accuracy, consistency and scalability. Importantly, this platform will allow our customers to evolve their individual feature strategies, while dramatically lowering the cost and complexity of developing new safety and user experience capabilities.”
The platform is designed to extend beyond automotive applications, with potential use cases across robotics and other human-machine interaction environments, including human-robot interaction (HRI) environments, where accurate and scalable perception of people and space is critical. The architecture also supports a mix-and-match approach to 3D technologies, enabling deployment flexibility as sensing hardware and use cases evolve.
Seeing Machines’ CES 2026 showcase reinforces the company’s commitment to advancing integrated, vision-based safety systems that support the next generation of intelligent, human-centred mobility.
Key CES 2026 Demonstration Features
Real-time digital reconstruction of an automotive cabin environment was showcased, including:
- 3 cameras covering 3 rows of seating with support for up to 7 vehicle occupants;
- Body size, shape and a full 3D pose solution for all occupants, including height and weight classification;
- Out-of-position detection for all occupants, for example, occupant reclining, feet on dash, near-airbag detection for driver;
- Seat configuration, for example, headrest presence, seat position and recline angle;
- Child seat detection across entire cabin; and
- Random object detection across cabin, for example, phones, bags and boxes.
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