What I enjoyed most in this piece is how it drags computer vision down from the pedestal of labs and military contracts into something artists and students can actually play with. The examples, from Krueger’s Videoplace to Levin’s own Messa di Voce, remind me that vision doesn’t have to mean surveillance or soulless AI pipelines. It can also mean goofy games, poetic visuals, or even awkward belt installations that literally stare back at you. I like this take, it makes technology feel less like a monolith and more like clay you can mold.
That said, I found the constant optimism about “anyone can code this with simple techniques” a little misleading. Sure, frame differencing and thresholding sound easy enough, but anyone who’s actually tried live video input knows it’s messy. Lighting ruins everything, lag creeps in, and suddenly the elegant vision algorithm thinks a chair is a person. The text does mention physical optimization tricks (infrared, backlighting, costumes), but it still downplays just how finicky the practice is. In other words, the dream of democratizing vision is exciting, but the reality is still a lot of duct tape and swearing at webcams.
What I take away is the sense that computer vision isn’t really about teaching machines to “see.” It’s about choosing what we want them to notice and what we conveniently ignore. A suicide detection box on the Golden Gate Bridge makes one statement; a silly limbo game makes another. Both rely on the same basic tools, but the meaning comes from what artists decide to track and why. For me, that’s the critical point: computer vision is less about pixels and algorithms and more about the values baked into what we make visible.