Unusual event recognition for mobile alarm system

Sooyeong Kwak, Guntae Bae, Kilcheon Kim, Hyeran Byun

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

2 Citations (Scopus)

Abstract

This paper proposes an unusual event recognition algorithm, which is a part of a mobile alarm system. Our systems focus on unusual event. When the system detects the unusual event, the photos of emergency situation are passed to the user's portable devices such as mobile phone or PDA along with event description to help the user's final decision. The system combines the foreground segmentation, object tracking and unusual event recognition to detect the Drop off, Abandon and Steal bag event. The event recognition module constructs the Bayesian network of each event and uses inference algorithm to detect the unusual event. The proposed system tested in PETS2006 and CAVIAR dataset. The proposed algorithm showed good results on the real world environment and also worked at real time speed.

Original languageEnglish
Title of host publicationComputational Science - ICCS 2007 - 7th International Conference, Proceedings
Pages417-424
Number of pages8
EditionPART 4
Publication statusPublished - 2007 Dec 1
Event7th International Conference on Computational Science, ICCS 2007 - Beijing, China
Duration: 2007 May 272007 May 30

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 4
Volume4490 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other7th International Conference on Computational Science, ICCS 2007
CountryChina
CityBeijing
Period07/5/2707/5/30

Fingerprint

Alarm systems
Personal digital assistants
Bayesian networks
Mobile phones
Object Tracking
Recognition Algorithm
Mobile Phone
Bayesian Networks
Emergency
Segmentation
Module

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Kwak, S., Bae, G., Kim, K., & Byun, H. (2007). Unusual event recognition for mobile alarm system. In Computational Science - ICCS 2007 - 7th International Conference, Proceedings (PART 4 ed., pp. 417-424). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4490 LNCS, No. PART 4).
Kwak, Sooyeong ; Bae, Guntae ; Kim, Kilcheon ; Byun, Hyeran. / Unusual event recognition for mobile alarm system. Computational Science - ICCS 2007 - 7th International Conference, Proceedings. PART 4. ed. 2007. pp. 417-424 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 4).
@inproceedings{3b5ff5f108694df29001bdf0896d7403,
title = "Unusual event recognition for mobile alarm system",
abstract = "This paper proposes an unusual event recognition algorithm, which is a part of a mobile alarm system. Our systems focus on unusual event. When the system detects the unusual event, the photos of emergency situation are passed to the user's portable devices such as mobile phone or PDA along with event description to help the user's final decision. The system combines the foreground segmentation, object tracking and unusual event recognition to detect the Drop off, Abandon and Steal bag event. The event recognition module constructs the Bayesian network of each event and uses inference algorithm to detect the unusual event. The proposed system tested in PETS2006 and CAVIAR dataset. The proposed algorithm showed good results on the real world environment and also worked at real time speed.",
author = "Sooyeong Kwak and Guntae Bae and Kilcheon Kim and Hyeran Byun",
year = "2007",
month = "12",
day = "1",
language = "English",
isbn = "9783540725893",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 4",
pages = "417--424",
booktitle = "Computational Science - ICCS 2007 - 7th International Conference, Proceedings",
edition = "PART 4",

}

Kwak, S, Bae, G, Kim, K & Byun, H 2007, Unusual event recognition for mobile alarm system. in Computational Science - ICCS 2007 - 7th International Conference, Proceedings. PART 4 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 4, vol. 4490 LNCS, pp. 417-424, 7th International Conference on Computational Science, ICCS 2007, Beijing, China, 07/5/27.

Unusual event recognition for mobile alarm system. / Kwak, Sooyeong; Bae, Guntae; Kim, Kilcheon; Byun, Hyeran.

Computational Science - ICCS 2007 - 7th International Conference, Proceedings. PART 4. ed. 2007. p. 417-424 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4490 LNCS, No. PART 4).

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

TY - GEN

T1 - Unusual event recognition for mobile alarm system

AU - Kwak, Sooyeong

AU - Bae, Guntae

AU - Kim, Kilcheon

AU - Byun, Hyeran

PY - 2007/12/1

Y1 - 2007/12/1

N2 - This paper proposes an unusual event recognition algorithm, which is a part of a mobile alarm system. Our systems focus on unusual event. When the system detects the unusual event, the photos of emergency situation are passed to the user's portable devices such as mobile phone or PDA along with event description to help the user's final decision. The system combines the foreground segmentation, object tracking and unusual event recognition to detect the Drop off, Abandon and Steal bag event. The event recognition module constructs the Bayesian network of each event and uses inference algorithm to detect the unusual event. The proposed system tested in PETS2006 and CAVIAR dataset. The proposed algorithm showed good results on the real world environment and also worked at real time speed.

AB - This paper proposes an unusual event recognition algorithm, which is a part of a mobile alarm system. Our systems focus on unusual event. When the system detects the unusual event, the photos of emergency situation are passed to the user's portable devices such as mobile phone or PDA along with event description to help the user's final decision. The system combines the foreground segmentation, object tracking and unusual event recognition to detect the Drop off, Abandon and Steal bag event. The event recognition module constructs the Bayesian network of each event and uses inference algorithm to detect the unusual event. The proposed system tested in PETS2006 and CAVIAR dataset. The proposed algorithm showed good results on the real world environment and also worked at real time speed.

UR - http://www.scopus.com/inward/record.url?scp=38149033688&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=38149033688&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:38149033688

SN - 9783540725893

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 417

EP - 424

BT - Computational Science - ICCS 2007 - 7th International Conference, Proceedings

ER -

Kwak S, Bae G, Kim K, Byun H. Unusual event recognition for mobile alarm system. In Computational Science - ICCS 2007 - 7th International Conference, Proceedings. PART 4 ed. 2007. p. 417-424. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 4).