Researchers at the Rowland Institute, Harvard, and McGovern Institute for Brain Sciences, MIT, are developing new, biologically-inspired vision systems taking advantage of faster computers. Their goal is to create vision systems for image understanding that can be as accurate as biological systems and more specifically the human visual system. The researchers have developed a new method that allows them to evaluate many different vision systems and quickly determine which are best suited for scene understanding. In a PLoS Computational Biology paper, the researchers show that their method performs better than current state-of-the-art computer vision systems when tested using standard data sets.
If you don’t want to read the paper, then you should at least watch the below video in its entirety. In the video, lead researcher David Cox explains at a high level how biological vision works and how their computational system mimics it to achieve the results presented in the paper.