HMM-Based Clustering for Learning Motion Patterns in Surveillance Video

@inproceedings{Swears2008HMMBasedCF,
  title={HMM-Based Clustering for Learning Motion Patterns in Surveillance Video},
  author={Eran Swears and Anthony Hoogs},
  year={2008}
}
When a video surveillance scene is observed over time, motion patterns can be learned and used to detect abnormal activity. The primary challenges include fragmented object tracks, sparse training data, unbalanced training data, and even temporal localization of a deviation. We present a novel approach to learning motion behavior in video, and detecting abnormal behavior, using hierarchical clustering of Hidden Markov Models (HMMs). A continuous stream of track data is used for online and on… CONTINUE READING