May. 26, 2021
Analyzing big data is crucial for organizations to make smarter data-driven decisions—but not all big data is created equally. It’s important to make the distinction between structured data and unstructured data:
In particular, videos are a prime example of unstructured data. Rather than the digital bits and bytes that make up video files, what’s really of interest is high-level information about what the video contains and depicts—from using facial recognition on individuals who appear in the video to detecting dangerous events with fire detection and fall detection.
But how can you extract this information in an automated, efficient manner? In other words, how can you turn videos into structured data?
To create structured data from videos, organizations are using sophisticated computer vision and artificial intelligence techniques. Computer vision platforms like Chooch can help anyone build state-of-the-art AI models that analyze videos frame by frame, detecting the people, objects, or events that you’ve trained them to look for.
Once you’ve gone through the AI training process, your computer vision model can automatically annotate each frame of the video. AI models can detect the motion of a person or object throughout the scene, as well as detect various actions and events. These annotations, which are saved as structured data, can then be searched and queried to retrieve the most relevant parts of the video.
It’s now easier than ever for your unstructured video data to become structured, thanks to computer vision and AI. Want to learn more about how Chooch can help? Get in touch with Chooch’s team of computer vision experts for an AI demo.