The world is generating massive amounts of video data, and mining it can be problematic. Automated search engines that rely on pre-tagged data, usually return too many low-quality matches and are often confined to specific types of objects. So, how can we clearly interpret data without spending hours of expert time to sequence areas of interest?
We’ve developed an innovative system for extracting high-level features from media, negating the need for pre-tagging the data. This approach allows us to search and compare any single image to find similarities, creating a flexible, focused user experience.
We developed Media Miner™. This is a tool that captures, analyses and segments huge quantities of video data to find common patterns, scenes and objects against a single image. Developed with a microservices architecture, Media Miner™ is scalable, easy to maintain and independently deployable.