Article

ViSE: Visual Search Engine Using Multiple Networked Cameras

Authors:

U. Park,

A. K. Jain,

I. Kitahara,

K. Kogure,

N. HagitaAuthors Info & Claims

ICPR '06: Proceedings of the 18th International Conference on Pattern Recognition - Volume 03

Pages 1204 - 1207

https://doi.org/10.1109/ICPR.2006.1176

Published: 20 August 2006 Publication History

Publisher Site

Abstract

We propose a Visual Search Engine (ViSE) as a semi-automatic component in a surveillance system using networked cameras. The ViSE aims to assist the monitoring operation of huge amounts of captured video streams, which tracks and finds people in the video based on their primitive features with the interaction of a human operator. We address the issues of object detection and tracking, shadow suppression and color-based recognition for the proposed system. The experimental results on a set of video data with ten subjects showed that ViSE retrieves correct candidates with 83% recall at 83% precision.

Cited By

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Behera NSa PBakshi SPadhy R(2022)Person re-identificationImage and Vision Computing10.1016/j.imavis.2022.104432122:COnline publication date: 1-Jun-2022
https://dl.acm.org/doi/10.1016/j.imavis.2022.104432
Cheng DGong YShi WZhang S(2018)Person re-identification by the asymmetric triplet and identification loss functionMultimedia Tools and Applications10.1007/s11042-017-5182-z77:3(3533-3550)Online publication date: 1-Feb-2018
https://dl.acm.org/doi/10.1007/s11042-017-5182-z
Wu AZheng WLai J(2017)Robust Depth-Based Person Re-IdentificationIEEE Transactions on Image Processing10.1109/TIP.2017.267520126:6(2588-2603)Online publication date: 1-Jun-2017
https://dl.acm.org/doi/10.1109/TIP.2017.2675201
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Index Terms

ViSE: Visual Search Engine Using Multiple Networked Cameras
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
      2. Computer vision tasks
        Scene understanding
  2. Machine learning
2. Information systems
  1. Information retrieval
    1. Information retrieval query processing

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Information

Published In

ICPR '06: Proceedings of the 18th International Conference on Pattern Recognition - Volume 03

August 2006

1242 pages

ISBN:0769525210

Publisher

IEEE Computer Society

United States

Publication History

Published: 20 August 2006

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Cited By

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Behera NSa PBakshi SPadhy R(2022)Person re-identificationImage and Vision Computing10.1016/j.imavis.2022.104432122:COnline publication date: 1-Jun-2022
https://dl.acm.org/doi/10.1016/j.imavis.2022.104432
Cheng DGong YShi WZhang S(2018)Person re-identification by the asymmetric triplet and identification loss functionMultimedia Tools and Applications10.1007/s11042-017-5182-z77:3(3533-3550)Online publication date: 1-Feb-2018
https://dl.acm.org/doi/10.1007/s11042-017-5182-z
Wu AZheng WLai J(2017)Robust Depth-Based Person Re-IdentificationIEEE Transactions on Image Processing10.1109/TIP.2017.267520126:6(2588-2603)Online publication date: 1-Jun-2017
https://dl.acm.org/doi/10.1109/TIP.2017.2675201
Yeh MChiu HWang J(2016)Fast medium-scale multiperson identification in aerial videosMultimedia Tools and Applications10.1007/s11042-015-2921-x75:23(16117-16133)Online publication date: 1-Dec-2016
https://dl.acm.org/doi/10.1007/s11042-015-2921-x
Kenk VMandeljc RKovačič SKristan MHajdinjak MPerš J(2015)Visual re-identification across large, distributed camera networksImage and Vision Computing10.1016/j.imavis.2014.11.00234:C(11-26)Online publication date: 1-Feb-2015
https://dl.acm.org/doi/10.1016/j.imavis.2014.11.002
Vezzani RBaltieri DCucchiara R(2013)People reidentification in surveillance and forensicsACM Computing Surveys10.1145/2543581.254359646:2(1-37)Online publication date: 27-Dec-2013
https://dl.acm.org/doi/10.1145/2543581.2543596
Bk SCorvéE EBréMond FThonnat M(2012)Boosted human re-identification using Riemannian manifoldsImage and Vision Computing10.1016/j.imavis.2011.08.00830:6-7(443-452)Online publication date: 1-Jun-2012
https://dl.acm.org/doi/10.1016/j.imavis.2011.08.008
Chen XHuang KTan T(2012)Object tracking across non-overlapping cameras using adaptive modelsProceedings of the 11th international conference on Computer Vision - Volume 210.1007/978-3-642-37484-5_38(464-477)Online publication date: 5-Nov-2012
https://dl.acm.org/doi/10.1007/978-3-642-37484-5_38
Li WZhao RWang X(2012)Human reidentification with transferred metric learningProceedings of the 11th Asian conference on Computer Vision - Volume Part I10.1007/978-3-642-37331-2_3(31-44)Online publication date: 5-Nov-2012
https://dl.acm.org/doi/10.1007/978-3-642-37331-2_3
B$#261;k SCharpiat GCorvée EBrémond FThonnat M(2012)Learning to match appearances by correlations in a covariance metric spaceProceedings of the 12th European conference on Computer Vision - Volume Part III10.1007/978-3-642-33712-3_58(806-820)Online publication date: 7-Oct-2012
https://dl.acm.org/doi/10.1007/978-3-642-33712-3_58
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Recommendations

VISE: An Interface for Visual Search and Exploration of Museum Collections

ViSE: a virtual smart environment for usability evaluation

Catadioptric Stereo Using Planar Mirrors

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