Abnormal event analysis using patching matching and concentric features

Jun-Wei Hsieh*, Sin Yu Chen, Chao Hong Chiang

*Corresponding author for this work

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

Abstract

This paper proposes a novel patch-based approach for abnormal event detection from a mobile camera using concentric features. It is very different from traditional methods which require the cameras being static for well foreground object detection. Two stages are included in this system i.e., training and detection, for scene representation and exceptional change detection of important objects like paintings or antiques. Firstly, at the training stage, a novel scene representation scheme is proposed for large-scale surveillance using a set of corners and key frames. Then, at the detection stage, a novel patch matching scheme is proposed for efficient scene searching and comparison. The scheme reduces the time complexity of matching not only from search space but also feature dimension in similarity matching. Thus, desired scenes can be obtained extremely fast. After that, a spider-web structure is proposed for missing object detection even though there are large camera movements between any two adjacent frames. Experimental results prove that our proposed system is efficient, robust, and superior in missing object detection and abnormal event analysis.

Original languageEnglish
Title of host publicationKnowledge-Based and Intelligent Information and Engineering Systems - 13th International Conference, KES 2009, Proceedings
Pages411-420
Number of pages10
EditionPART 2
DOIs
StatePublished - 4 Dec 2009
Event13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2009 - Santiago, Chile
Duration: 28 Sep 200930 Sep 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5712 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2009
CountryChile
CitySantiago
Period28/09/0930/09/09

Keywords

  • Concentric features
  • Patch clustering
  • Scene clustering
  • Video surveillance

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