Computer vision is really different from how humans see the world. While we naturally process images, depth, and context with our brains, computers rely on algorithms and sensors to make sense of what they’re “seeing.” Humans can instantly recognize faces, emotions, and even artistic meaning without much effort, but computers need tons of data and training to even get close to that level of understanding. Plus, human vision adjusts easily to different lighting or angles, while computers often struggle unless the conditions are just right.
To help computers track or recognize what we want, we use techniques like edge detection, motion tracking, and pattern recognition. Edge detection helps separate objects from the background, while motion tracking follows movement across frames in a video. Pattern recognition is also huge—by training a model with a bunch of images, it can learn to recognize faces, shapes, or even specific objects. But to get accurate results, we usually have to clean up the data first, removing noise or adjusting lighting so the system doesn’t get confused.
The ability of computer vision to track and monitor things has a big impact on interactive art. Artists use it to create pieces that respond to movement or presence, making the experience more immersive and engaging. But at the same time, it raises ethical concerns—these same tools can be used for surveillance, sometimes without people knowing. So while computer vision opens up exciting possibilities for art, it also forces us to think about privacy and how we balance creativity with responsibility.