The main objective of computer vision is to give machines the ability to see and interpret the world. This has proven a much more complex task than initially expected. We take for granted our innate ability to interpret and classify the world around us. We are attempting to do in decades what took evolution millions of years. 
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.