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Explore our ground truth solution

Experience the infinite potential of our end-to-end solution for ground truth annotations.

We engage where we are most needed

With our award-winning end-to-end solution for ground truth generation, we are the ideal partner for your annotation success at every stage of your project!

Initial Consulting

We define the scope of your project together, including concrete requirements and specifications.

Proof-of-Concept

We carry out a small-scale annotation pilot to test feasibility of requirements and specifications of your project.

First Training

We annotate data volumes sufficient to train your perception of common sensor-setups and ADAS/AD functions.

Large-Scale Validation

We annotate high volumes of data to validate the functionality of your ADAS/AD projects and the detection of your sensors.

Ground truth use cases

Whether you work on a traffic sign detection, an emergency brake assist or any other function, understand.ai addresses all common ADAS/AD use cases across 2D, 3D or 2D/3D sensor fusion projects.

2D Driver Monitoring System

2D Driver Monitoring System

We utilize ground truth annotations to train and validate the computer vision algorithms in the 2D driver monitoring system. This ensures the algorithms can effectively learn and accurately detect and interpret real-time driver behavior for improved driver safety and accident prevention.

2D Driver Monitoring System

3D Dynamic Object Detection

We leverage ground truth annotated data to train and validate the detection, localizing and tracking of dynamic objects in a three-dimensional space for the development of reliable 3D dynamic object detection systems.

2D Driver Monitoring System

Lane Detection

We utilize ground truth data annotations to ensure accurate algorithm training for reliable detection and analysis of lane markings from a top-down or "bird’s eye" perspective.

2D Driver Monitoring System

Lane markings

We apply ground truth 2D or 3D polyline annotation to precisely depict an object's boundaries or trajectories and enable reliable detection and tracking capabilities e.g., of lane markings, lane edges or poles.

2D Driver Monitoring System

2D Traffic Sign Detection

We leverage ground truth data annotation to accurately label and annotate the boundaries and attributes of traffic signs in 2D images - enabling the reliable detection and classification of traffic signs with high precision.

2D Driver Monitoring System

2D/3D Sensor Fusion

We can address all use cases as 2D/3D sensor fusion projects by combining data from multiple 2D sensors, such as cameras or LiDAR to enhance perception of the environment in real-time.

    Ground truth annotation types

    2D Driver Monitoring System

    3D Bounding Boxes

    We provide ground truth data for labeling 3D bounding boxes, accurately annotating the position, size, and orientation of objects in a 3D space.

    2D Driver Monitoring System

    2D Bounding Boxes

    We annotate 2D bounding boxes, precisely marking the location and dimensions of objects in a 2D image.

    2D Driver Monitoring System

    2D Semantic Segmentation

    We provide ground truth data for 2D semantic segmentation, annotating each pixel in an image with the corresponding object class or category.

    2D Driver Monitoring System

    2D/3D Polylines

    We label 2D/3D polylines, accurately annotating the shapes and trajectories of objects such as lane markings, lane edges or poles.

    2D Driver Monitoring System

    2D & 3D Keypoints

    We provide ground annotations as 2D and 3D keypoints, precisely annotating the specific locations or landmarks of objects in both 2D images and 3D spaces.

    2D Driver Monitoring System

    Classificcations & Attributes

    We assign distinct classifications and attributes to categorize and provide additional  properties or information on the state of an object.

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      Quality assurance by design

      Through our carefully curated End-to-End Quality Assurance process, we prioritize quality at every step. Our seamlessly integrated automated quality validators and checkpoints streamline the annotation production pipeline for reliable precision and efficiency. Additionally, we strictly adhere to clear quality metrics, guaranteeing accuracy and reliability throughout the entire process.

      01

      Preparation

      Align specification

      02

      Prototype

      Specification meets expectation

      03

      Sign Off

      Ready for production

      04

      Production

      Annotation and delivery

      05

      Acceptance

      Quality right first time

        Reference case: Sensor Fusion

        Explore this following reference case to gain deeper insight of our successful collaboration with one of our costumers.

        Scenic view of a curving bridge over calm waters with a solitary vehicle, framed by rugged mountains and coastline

        In this reference case, we successfully implemented an innovative sensor calibration solution. We covered of a diverse range classes including vehicles, pedestrians, bi-wheelers, traffic lights, and traffic signs as well as over 50 attributes. We ensured seamless execution from inception to completion resulting in the successfull delivery of over 10 million annotations.

        The Challenge

        • This project needed a sensor calibration solution due to the lack of an exact timestamp match between different sensors
        • Consistent object tracking between the different sensors
        • Describing over 50 different attributes with a non-subjective definition to achieve consistency and mutual understanding between all stakeholders
        • Creating efficient, clear and automation friendly labelling specifications

        Key Facts

        • Professional customer consulting including the design the entire project and shaping of the labelling specifications
        • Fully managed end-to end project
        • Ground Truth Annotation of vehicles, pedestrians, bi-wheelers, traffic lights and traffic signs
        • Delivered in total over 10 million annotations

        Key Achievements

        • Achieved annotation quality target of 98%
        • Often over-delivered on throughput targets
        • Solved a series of data quality and calibration problems
        • Successfully applied various of automation components to reduce significantly manual effort
        • Developed and applied a lot of validation rules serving as automated quality check, to ensure the best possible annotation quality
        Bosch
        Highly accurate annotation is an indispensable prerequisite for supervised machine learning. We rely on the labeling service and tools from understand.ai.
        Dr. Florian Faion,
        Research Scientist LiDAR Perception
        VW
        understand.ai is not only software, you also get a dedicated team that is knowledgeable and confident to exchange competencies and creative solution-oriented approaches, which definitely enriched our work.
        Dr. Peter Schlicht,
        Project Manager AI-Technologies for automated driving
        Eindhoven University of Technology
        understand.ai responded very quickly and were able to provide high-quality annotations within the same day, for an appropriate price. I would definitely recommend understand.ai to researchers in a similar position.
        Prof. Veronika Cheplygina,
        Eindhoven University of Technology
        EnBW
        EnBW Barriersystems appreciates the high quality of image annotations by understand.ai - the personal communication, fast response and fit of individual user needs combined with fair pricing is just outstanding!
        Lars Ehlkes,
        Machine Learning Engineer
        Sensagrate
        Data annotation can be difficult and expensive without a dependable partner, who’s easy to onboard with your needs. The willingness of understand.ai to take customer feedback and apply it quickly to the business and the flexibility of their tools for cost and throughput growth helped us to get us where we wanted.
        Darryl Keaton II,
        Founder and President
        L&T Technologies Services
        There’s a lot of automation inside. The architecture of the UAI tooling takes full advantage of AI. The way it’s structured makes it scalable, able to support large teams of labelers and parallel annotation. It’s boosting our throughput capabilities and making our customers happy.
        Indrajit Sen,
        Vice President and Regional Head, DACH