Pattern discovery for video surveillance

Yunqian Ma, Pradeep Buddharaju, Mike E Bazakos

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

2 Scopus citations

Abstract

There is a need in many surveillance applications to automatically detect certain events, such as activities and/or behaviors exhibited by people, vehicle, or other moving objects. Existing systems require that every event be custom coded, predefined, into the computer system. We present a novel system that can automatically capture and define (learn) new events by pattern discovery, and further presents the events to the operator for confirmation. The operator checks for validity of the newly detected events and adds them into the event library. We also propose a new feature selection procedure that can uniquely identify important events such as people falling. We present experimental results on real dataset, which shows the effectiveness of the proposed method.

Original languageEnglish (US)
Title of host publicationAdvances in Visual Computing - First International Symposium, ISVC 2005, Proceedings
Pages347-354
Number of pages8
DOIs
StatePublished - Dec 1 2005
Externally publishedYes
EventFirst International Symposium on Advances in Visual Computing, ISVC 2005 - Lake Tahoe, NV, United States
Duration: Dec 5 2005Dec 7 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3804 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherFirst International Symposium on Advances in Visual Computing, ISVC 2005
CountryUnited States
CityLake Tahoe, NV
Period12/5/0512/7/05

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