People reidentification in a distributed camera network
Article No.: 52, Pages 1 - 4
Abstract
This paper presents an approach to the people reidentification problem in a camera network system. The reidentification or reacquisition problem consists essentially on the matching process of images acquired from different cameras. This work is applied in a monitored environment by cameras. This application is important to modern security systems, in which the targets presence identification in the environment expands the capacity of action by security agents in real time and provides important parameters like localization for each target. We used the targett's color and targett's interest points with features for reidentification. The satisfactory results were obtained from real experiments in public video datasets and synthetic images with noise.
References
[1]
}}http://www.wisdom.weizmann.ac.il/vision/SpaceTimeActions.html, 2008.
[2]
}}Object Reacquisition and Tracking in Large-Scale Smart Camera Networks, Viena, 2007. First ACM/IEEE International Conference on Distributed Smart Cameras.
[3]
}}http://www.hitech-projects.com/euprojects/cantata/datasets_cantata/dataset.html, 2008.
[4]
}}http://groups.inf.ed.ac.uk/vision/CAVIAR/CAVIARDATA1/, 2004.
[5]
}}N. Gheissari, T. B. Sebastian, and R. Hartley. Person reidentification using spatiotemporal appearance. In 2006 Conference on Computer Vision and Pattern Recognition (CVPR 2006), pages 1528--1535, 2006.
[6]
}}O. Hamdoun, F. Moutarde, B. Stanciulescu, and B. Steux. Person re-identification in multi-camera system by signature based on interest point descriptors collected on short video sequences. In ICDSC08, pages 1--6, 2008.
[7]
}}Herbert Bay, Tinne Tuytelaars, and Luc Van Gool. SURF: Speeded Up Robust Features. In Proceedings of the ninth European Conference on Computer Vision, May 2006.
[8]
}}T. Lindeberg. Feature detection with automatic scale selection. International Journal of Computer Vision, 30(2):79--116, November 1998.
[9]
}}D. Lowe. Distinctive image features from scale-invariant keypoints. In International Journal of Computer Vision, volume 20, pages 91--110, 2003.
[10]
}}K. Mikolajczyk and C. Schmid. Indexing based on scale invariant interest points. Computer Vision, 2001. ICCV 2001. Proceedings. Eighth IEEE International Conference on, 1:525--531 vol. 1, 2001.
[11]
}}K. Morioka, X. Mao, and H. Hashimoto. Global color model based object matching in the multi-camera environment. Intelligent Robots and Systems, 2006 IEEE/RSJ International Conference on, pages 2644--2649, 2006.
[12]
}}U. Park, A. K. Jain, I. Kitahara, K. Kogure, and N. Hagita. Vise: Visual search engine using multiple networked cameras. Pattern Recognition, International Conference on, 3:1204--1207, 2006.
[13]
}}A Multi-Camera Visual Surveillance System for Tracking of Reoccurrences of People, 2007.
[14]
}}P. H. Tu, G. Doretto, N. O. Krahnstoever, J. Rittscher, T. B. Sebastian, T. Yu, and K. G. Harding. An intelligent video framework for homeland protection, 2007.
[15]
}}G. Wei, V. A. Petrushin, and A. V. Gershman. Multiple-camera people localization in a cluttered environment. Multimedia Data Mining Workshop, 2004.
Index Terms
- People reidentification in a distributed camera network
Recommendations
People Reidentification in a Camera Network
DASC '09: Proceedings of the 2009 Eighth IEEE International Conference on Dependable, Autonomic and Secure ComputingThis paper presents an approach to the object reidentification problem in a camera network system. The reidentification or reacquisition problem consists essentially on the matching process of images acquired from different cameras. This work is applied ...
Online Tracking of People through a Camera Network
DICTA '11: Proceedings of the 2011 International Conference on Digital Image Computing: Techniques and ApplicationsTracking pedestrians through a network of cameras is a difficult and nuanced problem that is of significant interest in visual surveillance. This paper describes an online system for tracking multiple people as they move around a small camera network ...
Persistent people tracking and face capture using a PTZ camera
Pan---tilt---zoom (PTZ) camera is a powerful tool in far-field scenarios. However, most of the current PTZ surveillance systems require manual intervention to move the camera to the desired position. In this paper, we address the problem of persistent ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
October 2009
382 pages
ISBN:9781605588803
DOI:10.1145/1858477
- Conference Chairs:
- Fernando Antonio Mota Trinta,
- Pedro Porfírio,
- Program Chairs:
- Rudinei Goularte,
- Renata Pontin de Mattos Fortes
Copyright © 2009 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
- SBC: Brazilian Computer Society
In-Cooperation
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 05 October 2009
Check for updates
Qualifiers
- Short-paper
Conference
WebMedia '09
Sponsor:
- SBC
WebMedia '09: XV Brazilian Symposium on Multimedia and the Web
October 5 - 7, 2009
Ceará, Fortaleza, Brazil
Acceptance Rates
Overall Acceptance Rate 270 of 873 submissions, 31%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 98Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 18 Jan 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in