Perceptual Data Mining
This talk describes my work in Perceptual Data Mining (PDM), a bottom-up data-driven framework for bootstrapping visual intelligence in novel environments. This work is focused on developing computational analogs for basic human perception and exploiting the strengths of computers to take full advantage of these capabilities. This research has centered on the development of systems that are capable of: automatically tracking multiple objects in real-time across multiple overlapping and non-overlapping cameras in unstructured indoor and outdoor environments; automatically modeling the types of objects in a particular environment; automatically modeling the activities that these objects perform; learning patterns of the activities over extended periods of time; and detecting unusual objects or behavior. Even without supervision, this system can create a compact description of the objects and activities in an environment that enables effective query retrieval. With minimal supervision, this system can communicate and summarize the activity in an environment. More information: http://www.csail.mit.edu/~stauffer/