Camio Interest-based Video Compression is a way to vary the video encoding, resolution, storage, and analyses based on the interest-level of what's actually happening in the video event. For example, a person approaching the rear entrance of a business at 2am is more important to capture in HD, store in the cloud, and analyze fully than a leaf blowing in the wind.
Traditional video encoding works at the pixel level to reduce video to its most compact representation. But Camio's Machine Learning ranks the interest of each event in real-time to make the optimal choices for the most cost-effective video surveillance.
For example, the camera below intentionally excludes passing street traffic and focuses only on people approaching on the sidewalk. Watch as the video switches from low resolution time lapse to full resolution as soon as the man approaches the monitored region of the scene:
Machine Learning automatically switches from timelapse → HD video when something interesting happens for the best bandwidth efficiency.