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An information retrieval approach to identifying infrequent events in surveillance video

Authors:

Suzanne Little,

Iveel Jargalsaikhan,

Noel E. O'Connor,

Alan F. Smeaton,

Jun LiuAuthors Info & Claims

ICMR '13: Proceedings of the 3rd ACM conference on International conference on multimedia retrieval

Pages 223 - 230

https://doi.org/10.1145/2461466.2461503

Published: 16 April 2013 Publication History

Abstract

This paper presents work on integrating multiple computer vision-based approaches to surveillance video analysis to support user retrieval of video segments showing human activities. Applied computer vision using real-world surveillance video data is an extremely challenging research problem, independently of any information retrieval (IR) issues. Here we describe the issues faced in developing both generic and specific analysis tools and how they were integrated for use in the new TRECVid interactive surveillance event detection task. We present an interaction paradigm and discuss the outcomes from face-to-face end user trials and the resulting feedback on the system from both professionals, who manage surveillance video, and computer vision or machine learning experts. We propose an information retrieval approach to finding events in surveillance video rather than solely relying on traditional annotation using specifically trained classifiers.

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Cited By

Spanias ANarayanaswamy VForzani ERaupp GKellam NO'Donnell MBarnard WLarson JO'Connor NDunne NDaniels SLittle S(2022)The ASU-DCU International Research and Workforce Development Program on Sensors and Machine Learning2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA)10.1109/IISA56318.2022.9904409(1-6)Online publication date: 18-Jul-2022
https://doi.org/10.1109/IISA56318.2022.9904409
Silva de Oliveira CSanin CSzczerbicki E(2020)Image Representation for Cognitive Systems Using SOEKS and DDNA: A Case Study for PPE ComplianceIntelligent Information and Database Systems10.1007/978-3-030-41964-6_19(214-225)Online publication date: 4-Mar-2020
https://doi.org/10.1007/978-3-030-41964-6_19
Kader MBoedihardjo AHossain M(2019)F2ConText: how to extract holistic contexts of persons of interest for enhancing exploratory analysisKnowledge and Information Systems10.1007/s10115-018-1304-961:1(363-396)Online publication date: 1-Oct-2019
https://dl.acm.org/doi/10.1007/s10115-018-1304-9
Show More Cited By

Index Terms

An information retrieval approach to identifying infrequent events in surveillance video
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks
        Video summarization
2. Mathematics of computing
  1. Information theory

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Information & Contributors

Information

Published In

cover image ACM Conferences

ICMR '13: Proceedings of the 3rd ACM conference on International conference on multimedia retrieval

April 2013

362 pages

ISBN:9781450320337

DOI:10.1145/2461466

General Chairs:
Ramesh Jain
University of California, Irvine, USA
,
Balakrisknan Prabhakaran
University of Texas at Dallas, USA
,
Program Chairs:
Marcel Worring
University of Amsterdam, The Netherlands
,
John Smith
IBM Research, New York, USA
,
Tat-Seng Chua
National University of Singapore

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGMM: ACM Special Interest Group on Multimedia

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 April 2013

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ICMR'13

Sponsor:

SIGMM

ICMR'13: International Conference on Multimedia Retrieval

April 16 - 20, 2013

Texas, Dallas, USA

Acceptance Rates

ICMR '13 Paper Acceptance Rate 38 of 96 submissions, 40%;

Overall Acceptance Rate 254 of 830 submissions, 31%

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Cited By

Spanias ANarayanaswamy VForzani ERaupp GKellam NO'Donnell MBarnard WLarson JO'Connor NDunne NDaniels SLittle S(2022)The ASU-DCU International Research and Workforce Development Program on Sensors and Machine Learning2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA)10.1109/IISA56318.2022.9904409(1-6)Online publication date: 18-Jul-2022
https://doi.org/10.1109/IISA56318.2022.9904409
Silva de Oliveira CSanin CSzczerbicki E(2020)Image Representation for Cognitive Systems Using SOEKS and DDNA: A Case Study for PPE ComplianceIntelligent Information and Database Systems10.1007/978-3-030-41964-6_19(214-225)Online publication date: 4-Mar-2020
https://doi.org/10.1007/978-3-030-41964-6_19
Kader MBoedihardjo AHossain M(2019)F2ConText: how to extract holistic contexts of persons of interest for enhancing exploratory analysisKnowledge and Information Systems10.1007/s10115-018-1304-961:1(363-396)Online publication date: 1-Oct-2019
https://dl.acm.org/doi/10.1007/s10115-018-1304-9
de Oliveira CSanin CSzczerbicki E(2018)Cognition and Decisional Experience to Support Safety Management in WorkplacesInformation Systems Architecture and Technology: Proceedings of 39th International Conference on Information Systems Architecture and Technology – ISAT 201810.1007/978-3-319-99996-8_24(266-275)Online publication date: 28-Aug-2018
https://doi.org/10.1007/978-3-319-99996-8_24
de Oliveira CSanin CSzczerbicki E(2017)Hazard Control in Industrial Environments: A Knowledge-Vision-Based ApproachInformation Systems Architecture and Technology: Proceedings of 38th International Conference on Information Systems Architecture and Technology – ISAT 201710.1007/978-3-319-67223-6_23(243-252)Online publication date: 1-Sep-2017
https://doi.org/10.1007/978-3-319-67223-6_23
Akpınar SAlpaslan F(2015)Optical flow-based representation for video action detectionEmerging Trends in Image Processing, Computer Vision and Pattern Recognition10.1016/B978-0-12-802045-6.00021-1(331-351)Online publication date: 2015
https://doi.org/10.1016/B978-0-12-802045-6.00021-1
Nieto MOrtega JCortes AGaines S(2014)Perspective Multiscale Detection and Tracking of PersonsProceedings of the 20th Anniversary International Conference on MultiMedia Modeling - Volume 832610.1007/978-3-319-04117-9_9(92-103)Online publication date: 6-Jan-2014
https://dl.acm.org/doi/10.1007/978-3-319-04117-9_9
Jargalsaikhan IDirekoglu CLittle SO'Connor N(2014)An Evaluation of Local Action Descriptors for Human Action Classification in the Presence of OcclusionProceedings of the 20th Anniversary International Conference on MultiMedia Modeling - Volume 832610.1007/978-3-319-04117-9_6(56-67)Online publication date: 6-Jan-2014
https://dl.acm.org/doi/10.1007/978-3-319-04117-9_6

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