The Alice camera is targeting a different type of creative and camera user.

“By applying computational photography to the Micro Four Thirds system we want to give people image quality more like that of a full-frame camera, at the price, size, and weight of an MFT camera…” states Liam Donovan, CTO of Alice Camera in an interview with us. In my 12 years of journalism, I can say that’s a very big claim. For the future of the camera market, I’m hoping Alice Camera can hold themselves true to it. Alice Camera is being funded on IndieGogo and promises to be completely different.

You talk about how the AI chip will help with things like color, focusing, and more. Can we assume that the focusing is involving things like faces and animals? Or is it more advanced where it can just track moving subjects in different ways? Can you also talk a bit more about color, please?

Liam: Autofocusing is a complicated process that consists of two stages, the first is about deciding which part of the frame to focus on, and the second is about deciding how far to move the lens and in which direction. Most modern mirrorless cameras use relatively primitive AI to do the first of these by identifying certain features in the frame, usually human eyes, and then use either contrast or phase detection techniques to do the second.

With Alice, we are using end-to-end trained AI techniques to do both parts of autofocusing. Our algorithms learn from very large numbers of correctly focused images how to find which part of the image should be in focus, and how to adjust the lens to bring that part of the image into focus. We don’t program it explicitly to focus on eyes or faces, we train it to do so when appropriate by showing it lots of images where the eyes are in focus. With these techniques, the camera is able to learn how to focus a little bit more like the way a human learns how to focus, by looking at the image directly and comparing it with prior knowledge and experience of what a focussed image should look like.

With color, we are using AI techniques to replicate the transformations performed by a skilled human retoucher automatically in real-time on the camera. These algorithms learn how to make local, context-aware adjustments to the image from large numbers of before/after pairs of processed images, and produce the sort of effects that have previously only been possible with skilled use of software like Lightroom.

For photographers, you can think of it like automatic color-aware dodging and burning. For filmmakers, you can think of it almost like a locally adaptive LUT applied to the raw video on-camera before compression. While these algorithms are very powerful we are deliberately limiting them from being able to fabricate details or manipulate reality as some AI techniques can, and we are making sure all our algorithms follow our four guidelines, to be natural, conservative, expressive, and controllable.

Can you talk to us about the build quality of Alice Camera? Is there weather resistance built-in?

Liam: The camera is made from CNC-machined aluminum and feels very solid in the hand. While it will not be fully weather-sealed, it will have some protection from water and weather damage.

Why did you choose Micro Four Thirds? Is the system built more for video or stills?

Liam: Micro Four Thirds sits at something of a sweet spot for what we are trying to do. MFT sensors are much larger than those found in smartphones and produce excellent image quality, certainly enough to be considered professional, however, they are much smaller and cheaper than high-end full-frame sensors. Crucially, MFT lenses are a lot smaller and lighter, and there is a huge variety of them available. By applying computational photography to the Micro Four Thirds system we want to give people image quality more like that of a full-frame camera, at the price, size, and weight of an MFT camera, and with the modern experience and connectivity of a smartphone.

...