[DaiPlusPlus]

This article struck a personal note with me because around the same time (2008-2012) I was really getting into vision, and even got published as an undergrad for imaging sensor fusion work (...my first, only, and likely last only meaningful contribution to my species); while the wider MV/CV community was making incremental gains every few years (anyone else remember Histogram-of-Oriented-Gradients?), that's what they were: incremental (I also remember my research-supervisor recounting how the patent on SIFT probably held back the entire field by a decade or two, so yes - things were slow-moving...

...until a few years ago when:

> Computer vision has been consumed by AI.

...but "AI" is an unsatisfying reduction. What does it even mean? (and c'mon, plenty of non-NN CV techniques going back decades can be called "AI" today with a straight-face (for example, an adaptive pixel+contour histogram model for classifying very specific things).

My point is that computer-vision, as a field, *is* (an) artificial-intelligence: it has not been "consumed by AI". I don't want ephemeral fad terminology (y'know... buzzwords) getting in the way of what could have been a much better article.

[usgroup]

I expect he just means deep and foundational models for vision, which is true: they dominate.

[ripe]

You are right: Computer Vision was always one of the original fields of AI research. The International Journal of Computer Vision was established in 1987 and it remains a premier outlet.

Today the word "AI" has itself been hijacked by marketers of ANN-based techniques, so when the article uses that term, it confuses people who don't know any better.

[ludicrousdispla]

>> computer-vision, as a field, is (an) artificial-intelligence

A lot of our visual perception happens on the retina and in the 'processing pipeline' before reaching the brain.

Margaret Livingstone provides an excellent overview in her book "Vision and Art" and she takes a view similar to yours.

[ncruces]

A lot of CV that used to be analytical (and benchmarked for metrics on synthetic data) is being replaced by train model on synthetic data to give answer.