
Movement & Behaviour
Understand how objects move and interact. Predict behaviour in video footage.
- Autonomous vehicles
- Traffic surveillance
- Human pose estimation
State-of-the art object tracking and interpolation features accelerates your video training data creation. Keep track of objects as they enter and leave the frame. Classify actions.
Encord's tools support video labelling for a variety of industries such as government, medical imaging, and smart cities.
Understand how objects move and interact. Predict behaviour in video footage.
Track multiple objects as they enter and leave the frame.
Classify events for specific frame intervals in video.
KCL used Encord to achieve a 6.4x average increase in labelling efficiency for GI videos.
We built Encord to support you as your data pipelines scale.
Flexible tools
Automated labelling
Configurable ontology
Quality
Collaborative workflows
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Our object tracking and interpolation features keep track of unique instance IDs through an entire video, and help to make the most of your human labels.
Our APIs & SDK allows for easy building of workflow scripts to converge quickly to successful data strategies. Set up complex pipelines and integrations within minutes.
Use automation to save on human supervision and enhance quality.
Encord has developed a wide range of automation features to annotate datasets to the highest quality standards to reduce the bottleneck of manual labour in the annotation process. These features include proprietary sampling, tracking, interpolation, auto-segmentation algorithms, and several intelligent heuristics. However, the core of our technology is a novel approach we call micro-models.
We believed there must be a better way to make AI practical from first starting the company. We have devised a unique and effective methodology for automating and streamlining the tasks related to preparing and managing quality training data.
In contrast to traditional machine learning models that require large quantities of data and are fit for robustness and generalisability, our micro-models are tightly scoped and over-fit to narrow tasks and data distributions.
Our technology allows you to train micro-models in only a few minutes, starting with just a handful of labels, and then ensemble many micro-models together to cover your complete set of labelling tasks. Our platform allows you to assemble micro-models to cover arbitrarily complex annotation tasks.