This blog post series explains in simple words the technologies associated with image recognition.
Image tagging is possibly the most widely used technology, being related to the organization of visual content which every large visual database needs. It automatically assigns keywords and tags to images and videos and can be applied to millions of visuals, which alternatively would require days of tedious and repetitive manual work. For this to happen a computer algorithm is trained with a huge amount of visuals and it “learns” from them, starting to recognize the people, objects, places or other attributes it has been trained with.
In this short video, Imagga CEO, Georgi Kadrev talks about image tagging and its applications.
Image tagging is often times combined with a similar technology that puts the images into relevant categories, called image categorization. This solves a major pain for companies operating with massive image databases – it provides fast and consistent image keywording, which is critical to image searchability.
Using our own Image Recognition API we created a free plugin for Adobe Lightroom to make it accessible to photographers who need to have control over their photo collections. Wordroom automatically offers diverse keywords with high accuracy and users can add them to the image’s metadata with a single click. Learn more about how to use Wordroom here.
Industries that use image tagging extensively include stock photography and photo sharing, DAM, advertising, commerce and retail, travel and booking platforms, real estate and more. Picture tagging has application in virtually any platform or system that operates with a large image or video database and wants to have control over their visual content.
Coming up in the next episode is Content Moderation.