Object Detection
(2D/3D)
For annotation that helps on Object Detection, our team uses Bounding Box & Polygon annotations for accurate identification & classification of objects like Vehicles, Pedestrians & Traffic Lights. This helps in identifying & localizing various objects in the scene, allowing the autonomous vehicle's perception system to understand its surroundings.
Vehicle
Keypoint
Keypoint Annotation on vehicles involves labeling specific points like Headlights, Doors, Tail Lights, Wheels, etc. By annotating key points on vehicles, AI algorithms can precisely locate & track these specific points.
Drivable Region & Road Boundaries Annotation
For Drivable Region & Road Boundaries Annotation, our team uses Polyline & Polygon annotation to mark the Lanes, Drivable Region & Boundaries on the images. This annotated data serves various purposes, including training autonomous vehicles for lane detection, path planning & understanding road infrastructure & is very helpful for ADAS services.
License Plate Annotation
Labelling license plate regions in images or video frames & transcribing the text. It facilitates automatic license plate recognition systems, enabling accurate identification & extraction of plate information for vehicle tracking, law enforcement & traffic management purposes.
Vehicle Tracking On Video Annotation
Vehicle Tracking For Video Annotation involves annotating the vehicle’s positions & trajectories across frames, utilizing bounding boxes or key points. This technique facilitates the analysis of vehicle behaviour, traffic flow & interactions, enhancing understanding & enabling applications like autonomous driving & traffic management.
Full Scene Labelling
Full Scene Labelling is one of the most complex annotation services wherein our team annotates all the objects, entities & attributes present in the image. This service enables the vehicle to detect & track objects, recognize & interpret all the exterior & interior objects including traffic signs, road markings, sky vegetation, cars, poles, wires, etc.
Sensor Fusion Annotation
Sensor Fusion Annotation involves annotation of synchronized data from multiple sensors such as cameras, LiDAR & RADAR. It provides ground truth for developing perception systems by accurately labelling objects based on fused sensor data.
House Number Annotation
Using bounding box annotation techniques, our annotators labeled house numbers within images, focusing on the "House Number" class. This data helps autonomous vehicles in precise navigation and reaching destinations accurately.