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Joint abnormal blob detection and localization under complex scenes

  • Tian Wang
  • , Keyu Lai
  • , Ce Li*
  • , Hichem Snoussi
  • *Corresponding author for this work
  • Beihang University
  • Lanzhou University of Technology
  • Xi'an Jiaotong University
  • Université de technologie de Troyes

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, an algorithm is proposed to detect the abnormal event in the form of rectangular blob in global images. Observing the status of the varying blobs, unusual behavior can be monitored and alarmed. A method extracting blobs from crowded video scenes is proposed, the covariance matrix descriptor fuses the image intensity and the optical flow to encode moving information and image characteristics of a blob. After characterizing normal behaviors of blobs or frames in a learning period, the nonlinear one-class SVM algorithm locates the abnormal blobs intra frame. The method is applied to detect abnormal events on several video surveillance datasets, and get promising results.

Original languageEnglish
Title of host publicationIntelligent Computing Theories and Methodologies - 11th International Conference, ICIC 2015, Proceedings
EditorsDe-Shuang Huang, Vitoantonio Bevilacqua, Prashan Premaratne
PublisherSpringer Verlag
Pages283-292
Number of pages10
ISBN (Print)9783319221793
DOIs
StatePublished - 2015
Event11th International Conference on Intelligent Computing, ICIC 2015 - Fuzhou, China
Duration: 20 Aug 201523 Aug 2015

Publication series

NameLecture Notes in Computer Science
Volume9225
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Conference on Intelligent Computing, ICIC 2015
Country/TerritoryChina
CityFuzhou
Period20/08/1523/08/15

Keywords

  • Abnormal blob localization
  • Blob extraction
  • Covariance matrix descriptor
  • One-class SVM

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