Portfolio
Explore our latest Projects Showcase.
LIDAR Annotations
Annotations
• 3D Semantic Segmentation
• Object detection & tracking with 3D boxes
• Object Classification
• Lane detection
• Image and Video Annotation
• 2D – 3D Linking
Bounding Box
Annotations
Data annotation for ego vehicles involves labeling lane markings, types, and traffic signs to enhance navigation. Bicycle lane annotations focus on dedicated lanes, shared usage, and cyclist interactions. Opposite-direction traffic requires marking lane directionality and conflict points. Divergence annotations highlight split and merging lanes, along with relevant visual cues. Accurate and consistent annotations are crucial for training effective machine-learning models in traffic scenarios.
Lane detection
Annotations
Lane detection data annotations involve labeling lane markings, including solid and dashed lines, to aid in vehicle navigation. Different lane types (e.g., turn lanes, bike lanes) must be clearly identified. Annotations should include lane boundaries, curvature, and width for accurate model training. Additionally, environmental factors like road conditions and markings should be noted. Consistent and precise annotations are essential for developing reliable lane detection algorithms in autonomous vehicles.