Computer vision is an incredibly broad field that seeks to extract information from images and video.  Even low-level vision problems such as image segmentation and optical flow have presented significant challenges to early researchers. Consequently, researchers have put forth a plethora of creative and unique approaches that have been pruned and refined over the years. This work explores some foundational algorithms in object detection and optical flow. In particular, we analyze the "You only look once" (YOLO) algorithm for object detection, as well as a more antiquated variational optical flow method by Brox et. al.