Supercharging your image: Machine learning for photography applications
Advanced capabilities for image retrieval and processing are relatively new and powered to a large extent by advances in machine learning technology. We present a brief history of this space, and share the story of how Shutterstock has embraced this technology and what it does for them.
A picture is worth a thousands words. Whether this cliché should always be taken at face value may be debatable, but the fact is that images are a key component of telling stories and getting attention.
While applications such as full text search have been helping users efficiently find the documents they need for a while now, similar applications for images have been lagging.
Documents can be indexed, summarized and compared with relative ease, which means document applications can be built with similar ease. Images on the other hand are harder to describe, and require much more storage and compute power to process.
Progress in storage and compute has resulted not only in increased ability to store images, but it has also unlocked previously unavailable capabilities. Pioneered by tech juggernauts such as Google and Microsoft, image applications powered by machine learning are finding their way to photography professionals.