Keylabs: A Platform Designed for Video Annotation
Video annotation supports many of the exciting AI applications that are changing our world. By labelling video footage frame by frame we allow computer vision models to understand a dynamically changing world. However, video annotation can be uniquely difficult. Even small pieces of training video can contain thousands of individual frames, all of which need to be precisely labelled.
As a result, video annotation can be a challenge for organisations of all sizes. Keylabs is a platform created to help with this challenge. Boasting unique features with competitive video annotation tool pricing, Keylabs helps streamline training dataset creation and improve label quality.
Video Annotation Types
Keylabs allows AI developers to craft exceptional datasets. The Keylabs platform features a full suite of video annotation methods, matching up with any video annotation tool online.
Keylabs data annotation tool online allows annotators to meet the specific needs of AI projects through a combination of labeling techniques. The key video annotation types are:
This annotation type divides each pixel in a video frame into classes. Annotators use the Keylabs annotation platform to outline objects or people in video frames.
These objects and people are then labeled accurately. Everything in the video frame is also treated in this manner, including background features. In this way information is added to every pixel in a piece of video training data.
This annotation type extends semantic segmentation by adding more detail to video training data. Instance segmentation means that every recurring instance of an object or person is given its own label and highlight colour. Instance segmentation adds more information to video training data. This can lead to higher performing AI models.
Video annotation techniques
There are a wide variety of video annotation techniques that can be applied to training data. Keylabs is a video annotation tool online that gives AI companies access to a full range of video annotation techniques. These techniques are used to create video training data for a huge number of different AI use cases. All are available with attractive data annotation tool pricing:
Bounding box annotation
To accomplish this technique annotators drag boxes around objects to locate them in a video frame. The advantage of bounding box annotation is that it is fast and easy to do over thousands of frames. However, it can be less accurate than segmentation methods.
This annotation technique allows annotators to capture more complex shapes. To accomplish polygon annotation annotators connect small lines around an object. This allows them to precisely define the shape of any object or person. As a result this technique is essential for segmentation methods.
This annotation technique is used to show the position of the human body in frames of training video. To achieve this technique annotators draw lines on human limbs joined together at joint positions.
Key points annotation
This technique is primarily used to find facial features in video frames. Annotators do key point annotation by adding points on the eyes, nose and mouth of people in video training data.
When AI developers want video training data to show linear structures like roads or pipelines they turn to lane annotation techniques. To do lane annotation, annotators draw parallel lines along these structures in each frame of the training video.
This annotation type links individual pixels to specific objects, allowing for annotations that are separated or contain gaps.
The Keylabs platform allows AI developers to combine the annotation methods and techniques shown above to create bespoke video training datasets.
A video annotation platform for a range of industries
Keylabs data annotation tool online supports AI developers in many industries.
Our powerful video annotation platform allows innovators to create precise training datasets for many different applications:
Annotated video data is essential for automated vehicles. Adding information to video frames allows AI models to learn how to move through dynamic environments.
AI models are being used to automate security systems. Annotated video data allows AI systems to identify dangerous objects and suspicious behaviour and alert security staff.
Annotated video data is supporting automated surgery technology. This technology could make operations safer in the near future.
Smart robots could improve the efficiency of assembly lines and manufacturing. Video data is essential for the continued development of this technology.
Automated drone technology has applications in a range of industries. Keylabs makes annotating video data for this technology easy and affordable.
Agriculture and livestock management
Video annotation allows AI models to recognize when animals are injured or sick. This can improve yields and animal welfare.
Applications for sports coaching and broadcasting need to be trained with accurately annotated video data.
Virtual wardrobe applications can make online shopping easier. Keylabs helps developers create exceptional training data for these applications.
Keylabs: A Powerful Tool for Video Annotation
Quality results from a team of annotation experts
Tap into decades of annotation experience from the team that created the Keylab video and image annotation tool.
Video annotation tool pricing
Data annotation tool pricing can be complex. As a result we offer competitive pricing to suit any AI project. Choose a smaller flexible package or take advantage of our volume based discounts. In our demo call we evaluate the needs of your project and identify the pricing options that are right for you.
Experience a video annotation tool built for scale
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