Practical Computer Vision

Abstract

The last half-decade ushered in a new era of vision research. Computer vision now works on real images, in natural environments, solving hard problems. But the technology is far from ubiquitous and many researchers are most concerned with getting the best performance on a handful of datasets. This hyperfocus on accuracy has largely turned vision into a numbers game and research tends toward complex, finely-tuned systems that are brittle and impractical in the real world. I focus on aspects of research that are often neglected in vision: speed, scalability, usability. I design new vision systems and algorithms from the ground up with the goal of making them useful in the real world. This involves high-level algorithm improvements, mid-level architectural design, and low-level optimization and approximation. It also involves educating the next generation of vision experts and giving them the tools to solve the problems they care about.