Learning temporal, relational, force-dynamic event definitions from video

  • Authors:
  • Alan Fern;Jeffrey Mark Siskind;Robert Givan

  • Affiliations:
  • School of Electrical and Computer Engineering, Purdue University, West Lafayette IN;School of Electrical and Computer Engineering, Purdue University, West Lafayette IN;School of Electrical and Computer Engineering, Purdue University, West Lafayette IN

  • Venue:
  • Eighteenth national conference on Artificial intelligence
  • Year:
  • 2002

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Abstract

We present and evaluate a novel implemented approach for learning to recognize events in video. First, we introduce a sublanguage of event logic, called k-AMA, that is sufficiently expressive to represent visual events yet sufficiently restrictive to support learning. Second, we develop a specific-to-general learning algorithm for learning event definitions in k-AMA. Finally, we apply this algorithm to the task of learning event definitions from video and show that it yields definitions that are competitive with hand-coded ones.