Registration algorithms are an essential component of many computer graphics and computer vision systems. With recent technological advances in RGBD sensors (color plus depth), an active area of research is in techniques combining color, geometry, and learnt priors for robust real-time registration. The goal of this course is to introduce the mathematical foundations and theoretical explanation of registration algorithms, in addition to the practical tools to design systems that leverage information from RGBD devices. We present traditional methods for correspondence computation derived from geometric first principles, along with modern techniques leveraging pre-processing of annotated datasets (e.g. deep neural networks). To illustrate the practical relevance of the theoretical content, we discuss applications including static and dynamic scanning/reconstruction as well as real-time tracking of hands and faces. An up-to-date version of the course notes, as well as slides and source code can be found at http://gfx.uvic.ca/teaching/registration.