5 AI uses in Photography

On our blog, we enjoy sharing the applications of Big Data and Artificial Intelligence in sectors that may surprise you. Previously, in “Dining with Data” we saw how customers may be able to order pizza with their eyes, and how doctors can be trained with Virtual Reality. Today, we are going to explore the world of digital photography. This market is expected to be worth $100.79bn by 2021, and as technology has developed, the industry has become more accessible to all. Below you can find out five examples where AI is helping both amateur and professional photographers when shooting and editing.

1) Portrait Mode

Taking photos with our phone has come a long way since Sharp launched the first camera phone, the “J-Phone” in 2000 (it’s worth reading the comments on the article for some entertainment). We can now shoot incredibly high-quality pictures and videos without the need for bulky camera equipment. One of the trends in recent years has seen many top-end cameras include two rear-cameras in order to offer a portrait mode that can achieve the “bokeh” effect (Japanese for blur) in which the subject is in focus and the background nicely blurred. However, in the future, we may see this switch again, and instead, an AI camera based on Machine Learning (ML) algorithms may replicate the effect. The Google Pixel 2 is one such phone already using this. These algorithms get smarter over time and have been “trained” to detect which part of the image is the subject in order to then blur the background.

      

We’re going to finish by looking at Arsenal, not the football team, but the “intelligent camera assistant” created by Ryan Stout. As you can see in the video below, Arsenal has some impressive features that revolve around its AI which controls the setting of the camera (exposure, aperture etc) based on the scene it is shooting. Once again, it uses Neural Networks as the foundation of its capabilities. Broadly speaking, the process involves detecting the content of the image, comparing these finding to the thousands of photos it has been trained on, and then suggests the best settings based on 18 factors. One example of where Arsenal comes into its own is “image stacking“, the process of taking multiple photos in order to capture all the detail in a scene at various exposures. The device takes a number of photos, merges them, and then exports them directly to the camera’s SD card. A quick glance of the comments on the YouTube video below shows the divide between those excited by this powerful tool and those who feel it is borderline “cheating” and takes the skill out of taking photos.