Computer Vision for the Road
Camera-based perception that understands roads, vehicles, pedestrians and traffic elements in real time.
Automata Mobility's computer vision stack turns camera streams into structured understanding of the driving scene. Detection, segmentation, depth and calibration models run on the vehicle edge to power lane keeping, collision warning, pedestrian safety and traffic-aware driving across two- and four-wheeler platforms.
Perception from pixels to scene graph.
A four-stage pipeline transforms raw camera frames into a validated, tracked understanding of the surrounding world.
Capture & Calibration
Multi-camera intrinsics/extrinsics and time sync.
Detection & Segmentation
Objects, lanes, signs and drivable area.
Depth & Geometry
Monocular and stereo depth for 3D awareness.
Scene Graph
Tracked entities passed to fusion and planning.
Building blocks of the stack.
Object Detection
Vehicles, cyclists and obstacles.
Lane Detection
Robust lane geometry in all conditions.
Pedestrian Detection
Vulnerable road user protection.
Traffic Sign Recognition
Speed, warning and regulatory signs.
Depth Estimation
3D structure from mono and stereo cameras.
Semantic Segmentation
Pixel-level scene classification.
Camera Calibration
Precision multi-camera alignment.
From signal to action.
Where it drives value.
ARAS
Two-wheeler vision safety.
ADAS
Passenger vehicle driver assistance.
Smart Mobility
Fleet, delivery and micro-mobility perception.
Engineered outcomes.
All-Condition Robustness
Trained across weather, night and glare.
Edge-Optimised
Quantised models tuned for on-vehicle inference.
Fusion Ready
Outputs align with radar and IMU inputs.
Explore the rest of the stack.
Build the next generation of mobility.
Partner with Automata Mobility to bring intelligent, safe and connected vehicles to the road.