automotive
LiDAR
Annotation for
Sensor Data
Tracking
United States
Overview
Overview
Expert LiDAR annotations improved Ouster’s product performance, enhanced their ML models, and helped them manage complex datasets, resulting in scalable, high-quality results.
performance
score
improvement
Client
Ouster is a US-based, leading provider of high-performance lidar sensors, leveraging digital technology to deliver 3D sensing solutions across various industries, including automotive, industrial, and robotics. Their advanced sensors enable accurate, real-time 3D data capture for enhanced automation and safety applications.
Challenges
The main challenge was delivering precise and scalable LiDAR annotation that seamlessly integrated into Ouster’s ML pipeline. The project required careful management of diverse datasets, ensuring that annotations met the high standards necessary for performance analysis and model training for the LiDAR tech provider.
Handling data from varied environments (interior/exterior, dynamic/static sensors)
Achieving consistent annotation quality for diverse use cases
Scaling the annotation process while maintaining accuracy
Ensuring seamless access and usability of annotated data for Ouster
Solution
To tackle the challenges, Label Your Data started with a small team first to build deep project expertise before scaling. Annotators used advanced tools to label LiDAR datasets, handling static and dynamic sensors across various environments. Continuous training and tool accessibility ensured consistent, high-quality results.
Provided 2D bounding boxes and 3D cuboids for the LiDAR scans provided by Ouster.
Integrated third-party LiDAR annotation tools for precise labeling.
Focused on both static and dynamic sensor data to cover varied use cases.
Scaled the annotation team in alignment with project growth demands.
Need High-Precision 3D LiDAR
Annotation at Scale?
Results
LiDAR annotation provided by the Label Your Data team enabled Ouster to perform accurate performance regression analysis. This significantly boosted their product performance. The annotations seamlessly fed into Ouster’s ML pipeline, exposing models to a wider array of data. The model now shows enhanced detection and tracking capabilities.
20% increase in product performance.
Achieved a 0.95 weighted F1 score.
Improved MOTA (multi-object tracking accuracy) by 15%.
Scaled the annotation team from 2 to 10 members with consistent quality.
Why AI Teams Choose Label Your Data
Data Annotation for Complex Environments
Rely on consistent, high-quality output for complex datasets, detailed taxonomies, and edge cases.
Structured Quality from Pilot to Production
Get quality engineered into every step through onboarding, evolving guidelines, QA, and continuous feedback.
Flexible and Scalable Operations
Adjust team capacity, project size, and delivery model as you scale, with no setup fees or long-term lock-ins.
An Integrated Delivery Partner
Align on goals, workflows, and expectations with a team that integrates into your process from day one.
Projects Led by Annotation Experts
Work with former annotators who understand annotation complexity, quality standards, and high-volume delivery.
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The precise LiDAR annotations and consistent quality, even as the project scaled, have been invaluable, significantly boosting our product performance and ML accuracy.
Dave Pike
Staff Software Engineer at Ouster
Trusted by ML Professionals
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