During the pandemic, I was really amazed by the process people had to go through before entering a space. Many places installed thermal face recognition systems at their entrances, and I remember lining up outside a mall, feeling confused about how it actually worked. While reading the article, that memory came back to me and helped answer the confusion I had back then. This experience made me realize the differences between computer vision and human vision. Instead of relying on perception, judgment, and context like a human would, computer vision processes visual information through algorithms that detect specific patterns, such as facial features and temperature readings. The system does not interpret situations the way humans do, it reads measurable data and produces a result based on programmed criteria. People had to stop, face the camera, and stand at the right distance so the system could read them accurately. In this case, the environment and people’s behavior were adjusted to be more legible to the algorithm, showing that while human vision is flexible and adaptable to different situations, computer vision relies on structured data and optimized conditions to function efficiently and consistently.
Computer vision’s ability to track and monitor people also changes how interactive art functions. Because the technology can detect movement, faces, or body position, it allows artworks to respond directly to the audience’s presence. However, as people differ from each other, the system produces various responses, creating multiple forms of interaction and monitoring. We can help the computer see or track what we are interested in by providing more labeled data so it can learn the patterns we want it to detect, improving visibility with good lighting and clear angles, using visual markers or cues, and controlling the environment to reduce background clutter and maintain proper distance.