Abstract: This talk will cover several research projects centered around the use of vision and motion capture for animation, recognition, and gaming. This includes human movements as diverse as subtle eye-blinks, lip-motions, spine-deformations, human walks and dances, politicians, base-ball pitchers, and online and offline crowd games. The technical content of the talk focuses on the trade-off between data-driven and crowd-sourced models of human motion vs. analytically derived and perceptually driven models using dancers, animators, linguists, and other domain experts. This is demonstrated by sub-pixel tracking in Hollywood productions, reading the body-language of public figures, visualizing the pitches of NY Yankees Mariano Rivera, and the making of mocap games in various cultures.