Video Annotation

We can perform the following annotation types on videos:

Bounding box annotation

This is the most common, fast, reliable and cost-effective annotation method.

Polygon annotation

This is what you need if you are dealing with irregular shapes and your project requires more precision than regular bounding box annotation.

Semantic segmentation

Do you need to group multiple objects of a single category as one entity? Then semantic segmentation might meet that need. Contact us to learn more, our specialists can help you to identify the right video annotation type for your project.

Skeletal annotation

Reveals body position and alignment. These are commonly used in sports analytics, fitness and security applications.

Key points annotation

Identify and mark key points of an object on videos, such as eyes, noses, lips, or even individual cells.

Lane annotation

Most commonly used for annotating roads, pipelines and rails, this is one of the annotation types most commonly used by car manufacturers today.

Instance segmentation

We can easily detect instances of each category and identify individual objects within these categories. Categories like “vehicles” are split into “cars,” “motorcycles,” “buses,” and so on.

Custom annotation

If your project requires a specific combination of annotation types, or even a new annotation type, we can easily achieve that for you. Or our exceptional R&D team can evaluate your project and create a completely new video annotation type based on your specific requirements.

Video annotation

Video significantly increases the annotation workload by multiplying the amount of images that must be labeled in a dataset. Each frame of video must be as precisely annotated as an individual image. This process can be sped up by making use of object interpolation techniques. Object interpolation algorithms track a labeled object through multiple frames, allowing annotators to create video annotations much more efficiently.

Video annotation with bounding box

This annotation technique identifies objects by drawing a rectangle around them, and then labeling them. A car, for example, will be located by a bounding box across each frame of video.

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Video annotation with polygon

Polygon annotation allows for added detail when annotating objects, particularly if they are not uniformly shaped.

Annotators can connect points around a complicated object, such as an animal, using this method.

Semantic segmentation on video

Video data can contain additional information for AI training by deploying semantic segmentation.

This technique separates each pixel in each frame into classes of objects.

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Instance segmentation on video

Instance segmentation promotes granularity in video data by identifying each individual case of a particular class of object in every frame.

For agricultural AI this might mean outlining and labeling each individual sheep across an entire piece of footage.

Video annotation with points

Often AI models are required to identify key points in video footage. To achieve this annotators work through thousands of frames locating important positions in each image.

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Video annotation with lines

Linear objects often need to be defined and labeled in video footage.

Line annotation outlines landmarks like roads in each frame, allowing AI models to discern the dimensions and locations of these features in a variety of contexts.

Skeletal video annotation

Charting and analysing the movements of the human body in video is an important application for machine learning models.

Skeletal annotation reveals how the body navigates from frame to frame.

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Industries that we serve

  • Automotive
    We can annotate videos that take place in a variety of weather conditions, in the day or the night, without missing a single detail.
  • Security
    CCTV footage annotation, traffic monitoring, person or object tracking through multiple cameras and video frames.
  • Aerial
    There are countless applications for drone AI, but these models require high quality datasets. We annotate drone footage for agricultural applications, object tracking, advanced monitoring systems, disaster monitoring and management and more.
  • Precision Agriculture and Livestock Management
    We have vast experience in farm drone footage annotation, real time crop monitoring and ripeness detection, as well as video footage annotation from farm cameras for livestock management and counting.

Video annotation

  • Medical
    Just tell us what your project requires, and we will deliver. We offer medical video collection and annotation by certified medical professionals.
  • Robotics
    From delivery robots to an “eye” in the production line, we can help you do it all. Our video annotation services are here to facilitate the countless applications of robotics AI.
  • Waste Management
    Video annotation for sorting facilities will help to identify what can and can’t be recycled without risking human exposure to potentially toxic or hazardous waste.
  • Sport
    VWe annotate videos for sport analytics and fitness applications, tracking every change in body position and alignment.
  • Retail
    The use cases for retail AI, trained through video annotation, are numerous. For example mapping customer’s paths through the store or tracking objects from security camera footage for loss prevention.

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