Subjects include fundamental representations, learning approaches, matching-based algorithms, human activity models for video, and large-scale recognition. Three lecture hours a week for one semester. Computer Science 381V and 395T (Topic: Visual Recognition) may not both be counted. Prerequisite: Graduate standing; a background in basic computer vision and machine learning is recommended.