Meet us at Computer Vision and Pattern Recognition June 16th-20th 2019 Long Beach, CA

LIDAR 3D Point Cloud Labeling

Visualize, label and track objects across frames in 3D point clouds for all types of LiDARs.

  • Sensor fusion support
  • Extra attributes for objects
  • 3D box tracking
  • Semantic segmentation

We support diverse use-cases

Playment transforms your raw dataset into annotated images with bounding boxes around objects of interest.

Object detection & tracking with 3D boxes

Get size, location, speed, pitch, yaw, heading and tracklets of objects accurate up to 1 cm with 3D boxes. Get 3D orientations including roll, pitch, yaw and heading along with class, dimensions and tracking label at high accuracy. Our class list is exhaustive and ever-growing.

3D Semantic Segmentation

Label every single point accurately with a definite class. Point level segmentation for your autonomous vehicles both indoor and outdoor environments. We also support subtle nuances such as instance level, drivable and pedestrian designated zones.

Object Classification

Classify each identified with additional attributes relevant for perception model to learn.

Lane detection

Polylines to distinguish various lanes in 3D point cloud map. Lane detection to annotate road demarcations for safe driving.

Hardwares we support

Built for Enterprise

Proprietary Quality Assurance

Multi-level quality checks
We have proprietary and unique QA processes for every annotation constructed from experience of annotating millions of objects. QA process is a combination of
  • Annotator reputation engine.
  • Maker-checker and consensus models.
  • Automatic checks to catch systemic errors.
  • Critical manual checks with statistical sampling.
Creative training of annotators
We work with our customers to draft a comprehensive annnotation policy and transform it into easy to learn training material. Our training software enables our project managers to train a huge workforce of annotators even on nuanced labeling concepts and time to time policy changes.
Multi-level quality checks
We have proprietary and unique QA processes for every annotation constructed from experience of annotating millions of objects. QA process is a combination of
  • Annotator reputation engine.
  • Maker-checker and consensus models.
  • Automatic checks to catch systemic errors.
  • Critical manual checks with statistical sampling.
Verification tools for customers' QC teams
We believe in providing complete transparency to our customers on data accuracy metrics. Playment's customer tools and dashboard facilitates checking of labeled output, annotation level feedbacks by your QC teams.

End-to-end Tech Support

Our engineers work so hard to fulfill all your custom requirements. Starting from supporting various sensor data formats to building complex annotation tools. We also set up unique data sharing modes so that you can focus on building and optimizing ML models.

Tech Support

Why choose Playment

With rigour quality checks, free repetition allowance, high-quality ground truth annotation and end-to-end project management we're confident you'll love us.

Guaranteed Quality

Definition, Process Excellence and Transparency are the three pillars of our accuracy promise.

Fully Managed Solution

Full suite of annotation tools with the help of project consulting, dedicated project management and tech support.

Competitive Cost

Playment uses machine learning models to perform semi-automatic labeling at a fraction of the cost of manual labeling.

Trusted by

We were very impressed with Playment’s ability to grasp complex requirements and quickly build custom tools to support it. Jitesh(Engagement Manager) was very helpful with sharing his domain expertise to formulate the solution.
Nikola Noxon
Senior Engineer, Daimler
Playment's fully managed approach has been critical in factoring the variability and scaling up our annotation requirements. Thanks to their tools and skilled workforce, we are extremely satisfied by the quality and turnaround time they have provided. I would highly recommend Playment.
Shmoolik Mangan
Algorithm Development Manager, Vayavision

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