Johns Hopkins University 3 credits Computer Science
This course provides an overview of fundamental methods in computer vision from a computational perspective. Methods studied include: camera systems and their modeling, computation of 3-D geometry from binocular stereo, motion, and photometric stereo, and object recognition, image segmentation, and activity analysis. Elements of machine learning and deep learning are also included. Practical application of these concepts is emphasized through written and programming homework assignments. Students will also have an opportunity to further explore concepts through a semester long project. Prerequisite(s): Intro to Programming, Linear Algebra & Probability/Statistics
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