Understanding dynamic scenes by hierarchical motion pattern mining

Lei Song*, Fan Jiang, Zhongke Shi, Aggelos K Katsaggelos

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

20 Scopus citations

Abstract

Our work addresses the problem of analyzing and understanding dynamic video scenes. A two-level motion pattern mining approach is proposed. At the first level, single-agent motion patterns are modeled as distributions over pixel-based features. At the second level, interaction patterns are modeled as distributions over single-agent motion patterns. Both patterns are shared among video clips. Compared to other works, the advantage of our method is that interaction patterns are detected and assigned to every video frame. This enables a finer semantic interpretation and more precise anomaly detection. Specifically, every video frame is labeled by a certain interaction pattern and moving pixels in each frame which do not belong to any singleagent pattern or cannot exist in the corresponding interaction pattern are detected as anomalies. We have tested our approach on a challenging traffic surveillance sequence containing both pedestrian and vehicular motions and obtained promising results.

Original languageEnglish (US)
Title of host publicationElectronic Proceedings of the 2011 IEEE International Conference on Multimedia and Expo, ICME 2011
DOIs
StatePublished - Nov 7 2011
Event2011 12th IEEE International Conference on Multimedia and Expo, ICME 2011 - Barcelona, Spain
Duration: Jul 11 2011Jul 15 2011

Publication series

NameProceedings - IEEE International Conference on Multimedia and Expo
ISSN (Print)1945-7871
ISSN (Electronic)1945-788X

Other

Other2011 12th IEEE International Conference on Multimedia and Expo, ICME 2011
CountrySpain
CityBarcelona
Period7/11/117/15/11

Keywords

  • LDA
  • Visual surveillance
  • anomaly detection
  • motion pattern analysis

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications

Fingerprint Dive into the research topics of 'Understanding dynamic scenes by hierarchical motion pattern mining'. Together they form a unique fingerprint.

Cite this