CS Colloquium: Why is Computer Graphics Hard? By Dr. Richard Zhang
Dr. Richard Zhang will be presenting the talk "Why is Computer Graphics Hard?" as part of SFU's School of Computing Science Colloquium series of research talks by faculty members and grad students.
Computer graphics is traditionally defined as a field which covers all aspects of computer-assisted image synthesis. Is computer graphics hard? An introductory class to graphics mainly teaches how to turn an explicit model description including geometric and photometric attributes into one or more images. Under this classical and arguably narrow definition, computer graphics corresponds to a ``forward'' (synthesis) problem, which is probably easier than the inverse (analysis) problem, one which computer vision traditionally battles with.
In this talk, before offering my new perspectives, let me first remind ourselves several well-known data challenges that are unique to graphics problems. Then, by altering the above classical definition of computer graphics, perhaps only slightly, I show that to do the synthesis right, one has to first solve various inverse problems. In this sense, graphics and vision are converging, with data and learning playing key roles in both fields. A recurring challenge however is a general lack of “Big 3D Data”, which graphics research is expected to address. Finally, I want to explore a new perspective for the synthesis problem to mimic a higher-level human capability than pattern recognition and understanding.
I hope to convince you that under these new views of the field, and as we explore perhaps its boundary, computer graphics can be pretty hard, and we are only starting to scratch the surface.