Video annotation for AI
Video annotation is the process of creating metadata in the form of labels for video clips. This type of annotation tags objects on a frame-by-frame basis. It is used to create datasets for computer vision models so they can identify images and extract the information needed to make accurate predictions.
Video annotation plays an important role in computer vision, the area of artificial intelligence that trains computers to interpret and understand the visual world. By using annotated or labeled images to train machine learning models, machines can accurately identify and classify objects and then respond to what they "see".
Computer vision applications include:
LXT for video annotation
With LXT, you can quickly build a reliable data pipeline to power your computer vision solutions and focus on building the technologies of the future. The combination of our annotation platform, managed crowd, and quality methodologies deliver the high-quality data you need so you can build more accurate AI solutions and accelerate your time to market. Every client engagement is customized to fit the needs of your specific use case.
Our video annotation services include:
Dialog and conversation tracking
Video classification
Video captioning
Video transcription
Translate the audio from videos into text for both short-form and long form videos to improve video captioning capabilities, search results and more. Support for various video types including YouTube and TikTok.
Secure services
With the accelerating volumes of data created daily and the number of potential threats on the rise, security is an increasing area of concern for organizations across all industries. Our platform and processes are designed to ensure the security of your data.
To meet the most stringent security requirements, our facilities are ISO 27001 certified and PCI DSS compliant. We also offer supervised transcription within a secure facility to safeguard your data. We will work closely with you to design a secure solution that meets your needs.