iMerit's 3D Point Cloud Solution

Discover how iMerit’s cutting-edge 3D point cloud technology automates annotation workflows by integrating multi-sensor data from LiDAR, Radar, and cameras. This video showcases innovative automation features designed to improve annotation accuracy, streamline validation, and enhance object detection.

Key Features Covered in the Demo:

Multi-Sensor Data Fusion:
Utilizes LiDAR, Radar, and camera data for a comprehensive perception system.
Enhances object detection and annotation accuracy with multi-source data integration.
Automated Point Cloud Merging:
Merges multi-frame point cloud data into a single, unified coordinate system.
Eliminates manual frame traversal, offering a holistic view of object sequences.
Improves efficiency by allowing users to visualize aggregated data over time.
Validation Automation:
Generates automatic validation reports summarizing annotation quality.
Identifies errors in high-quality annotation to ensure precision and consistency.
3D-to-2D Projection Automation:
Projects 3D cuboids onto 2D images, aligning LiDAR and camera data.
Simplifies object detection by providing clear visual references.
Automates bounding box creation, eliminating manual annotation steps.
Intensity Feature:
Intensity feature to bring forward objects on the scene with reflective surfaces. Helps in use cases such as "Lane Detection, Traffic Signs, Traffic Cones, Traffic Signals, VRU wearing reflective gear..."
Enhances object visibility by adjusting contrast settings.
Machine Learning-Powered Point Cloud Segmentation:
Automatically differentiates point cloud data into ground and non-ground points.
Reduces manual annotation errors and refines labeling accuracy.
Comprehensive Drawable Tools for 3D Annotation:
Supports 2D polygons, 2D bounding boxes, 2D cuboids, 3D polygons, 3D bounding boxes, and 3D cuboids and paintbrush
Linearly interpolates cuboid generation across frames for seamless tracking.
Provides attribute propagation for efficient scene labeling.