Reading on Computer Vision

As automation became one of the primary sector of human technology, computer vision has become an important field in the areas of computer science and interactive media studies. We have continuously seen a rapid development in algorithms to track movements and distinguish a certain specific figure among a crowd of people. As people gained depth knowledge in how computer vision works, more attempts to combine machine learning into the algorithm to automate the process has also been a high-interest for many aspiring computer scientists.

There are great uses with computer vision that can assist our lives, but relying it to replace our decision completely would be a problem – such as using computer vision system to find possible suspects. I was fascinated by the different applications and methods of computer vision, but I could not get rid of the thought of a recent issue on using facial recognition to identify suspected criminals. As Golan Levin says, “the reliability of computer vision algorithms is limited according to the quality of the incoming video scene, and the definition of a scene’s ‘quality’ is determined by the specific algorithms which are used to analyze it” (Levin). Yes, it is a technology that can be used in such cases, but I believe the technology is not just ready for such use to odd out human decision.

Met police’s facial recognition technology ‘96% inaccurate’

The issue of the above article may not be a problem – and could be forgotten in few decades – as our software and hardwares develop to overcome the quality and accuracy issues. However, the issue of “fully-trusting” the result of complex computer vision is a topic that we should continue to question.