THIS IS A BLOG OF YEZHOU YANG, A PH.D STUDENT AT UNIVERSITY OF MARYLAND, COLLEGE PARK.
MOST OF THE POSTS HERE ARE MY STUDY AND RESEARCH NOTES FOR QUICK ONLINE ACCESS. OCCASIONALLY, MY STUPID IDEAS WILL ALSO BE SHARED HERE.
He is a researcher from NIST and from his talk, I strongly felt that their research has a kind of Physics-style. In which way, his group has made a tremendous contribution to the area of face recognition.
His talk mainly about several face recognition challenges. He said there are four main problems in this area: Age, Expression, Illumination and ( I forgot...). I used to think face recognition is a well-solved problem, as it seems to be the most successful application of Computer Vision into business. However, from Jonathon, the face recognition problem is far away from being solved. Human can easily recognize a friend under several severely bad conditions, such as low illumination. However, the performance of face recognition program drops extraordinarily. Jonathon's team conducted an experiment of collecting good, acceptable and bad images containing static faces to evaluate several face recognition algorithms' performance.
I think future Computer Science will divided ( or maybe has already divided) into two parts, just like the Physics now: Experimental Computer Science and Theoretical Computer Science. For example, Machine learning belongs to Theory and Computer Vision is largely an Experimental one. Do more experiment rather than just analyze data on machines will be the main trend, which is my belief too.