Mimicking Human Camera Operators

We combine this information with tracked player positions to build a structured predictor. Given unseen player positions from a new game, we use the learned predictor to generate target pan-tilt-zoom values for a robotic camera.

Learn More

Learning Fine-Grain Spatial Models for Dynamic Sports Play Prediction

We consider the problem of learning predictive models for in-game sports play prediction. Focusing on basketball, we develop models for anticipating near-future events given the current game state. We employ a latent factor modeling approach, which leads to a compact data representation that enables efficient prediction given raw spatiotemporal tracking data.

Learn More