The purpose of this course is to introduce algorithms for 3D structure inference from 2D images. In many applications, inferring 3D structure from 2D images can provide crucial sensing information. The course will begin by reviewing geometric image formation and mathematical concepts that are used to describe it, and then move to discuss algorithms for 3D model reconstruction. The problem of 3D model reconstruction is an inverse problem in which we need to infer 3D information based on incomplete (2D) observations. We will discuss reconstruction algorithms which utilize information from multiple views. Reconstruction requires the knowledge of some intrinsic and extrinsic camera parameters, and the establishment of correspondence between views. We will discuss algorithms for determining camera parameters (camera calibration) and for obtaining correspondence using epipolar constraints between views. The course will also introduce relevant 3D imaging software components available through the industry standard OpenCV library.