The main objective of computer vision is to give machines the gift of sight as well as the capacity to understand visual input. This has proven a much more complex task than expected. We often take for granted the fact that our vision evolved biologically over millions of years, and we develop our ability to interpret and classify the world around us in early childhood.
In this episode Saurabh, Nikhil, and Melody discuss the emergence of computer vision as a discipline, the differences in the way that humans and computers “see” images, and the math behind the algorithms. Then they look at some examples of how computer vision is employed in everyday life in Snapchat filters, YouTube video buffering, medical diagnosis of x-rays, and the use of geospatial mapping for agriculture.