skip to main content
research-article

Large-Area, Multilayered, and High-Resolution Visual Monitoring Using a Dual-Camera System

Published: 07 January 2015 Publication History

Abstract

Large-area, high-resolution visual monitoring systems are indispensable in surveillance applications. To construct such systems, high-quality image capture and display devices are required. Whereas high-quality displays have rapidly developed, as exemplified by the announcement of the 85-inch 4K ultrahigh-definition TV by Samsung at the 2013 Consumer Electronics Show (CES), high-resolution surveillance cameras have progressed slowly and remain not widely used compared with displays. In this study, we designed an innovative framework, using a dual-camera system comprising a wide-angle fixed camera and a high-resolution pan-tilt-zoom (PTZ) camera to construct a large-area, multilayered, and high-resolution visual monitoring system that features multiresolution monitoring of moving objects. First, we developed a novel calibration approach to estimate the relationship between the two cameras and calibrate the PTZ camera. The PTZ camera was calibrated based on the consistent property of distinct pan-tilt angle at various zooming factors, accelerating the calibration process without affecting accuracy; this calibration process has not been reported previously. After calibrating the dual-camera system, we used the PTZ camera and synthesized a large-area and high-resolution background image. When foreground targets were detected in the images captured by the wide-angle camera, the PTZ camera was controlled to continuously track the user-selected target. Last, we integrated preconstructed high-resolution background and low-resolution foreground images captured using the wide-angle camera and the high-resolution foreground image captured using the PTZ camera to generate a large-area, multilayered, and high-resolution view of the scene.

References

[1]
A. Alahi, D. Marimon, M. Bierlaire, and M. Kunt. 2008. A master-slave approach for object detection and matching with fixed and mobile cameras. In Proceedings of the 15th IEEE International Conference on Image Processing (ICIP). 1712--1715.
[2]
M. Andriluka, S. Roth, and B. Schiele. 2008. People-tracking-by-detection and people-detection-by-tracking. In Proceedings of the 12th IEEE International Conference on Computer Vision and Pattern Recognition (CVPR). 1511--1522.
[3]
M. S. Arulampalam, S. Maskell, N. Gordon, and T. Clapp. 2002. A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking. IEEE Trans. Signal Process. 50, 2, 174--188.
[4]
O. Barnich and M. Van Droogenbroeck. 2011. ViBe: A universal background subtraction algorithm for video sequences. IEEE Trans. Image Process. 20, 6,1709--1724.
[5]
P. Baudisch, N. Good, V. Bellotti, and P. Schraedley. 2002. Keeping things in context: A comparative evaluation of focus plus context screens, overviews, and zooming. In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI). 259--266.
[6]
P. Baudisch, N. Good, and P. Stewart. 2001. Focus plus context screens: Combining display technology with visualization techniques. In Proceedings of the 14th Annual ACM Symposium on User Interface Software and Technology (UIST). 31--40.
[7]
P. N. Belhumeur, J. P. Hespanha, and D. J. Kriegman. 1997. Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection. IEEE Trans. Pattern Anal. Mach. Intell. 19, 7, 711--720.
[8]
M. Brown and D. G. Lowe. 2003. Recognising panoramas. In Proceedings of the 9th IEEE International Conference on Computer Vision (ICCV). 1218--1227.
[9]
Y. Cai, G. G. Medioni, and T. B. Dinh. 2013. Towards a practical PTZ face detection and tracking system. In Proceedings of the IEEE Workshop on Applications of Computer Vision (WACV). 31--38.
[10]
K.-W. Chen, C.-W. Lin, T.-H. Chiu, M. Y.-Y. Chen, and Y.-P. Hung. 2011. Multi-Resolution Design for Large-Scale and High-Resolution Monitoring. IEEE Trans. Multimedia. 13, 6, 1256--1268.
[11]
K.-W. Chen, C.-W. Lin, M. Y.-Y. Chen, and Y.-P. Hung. 2010. e-Fovea: A multi-resolution approach with steerable focus to large-scale and high-resolution monitoring. In Proceedings of the ACM International Conference on Multimedia (MM). 311--320.
[12]
C. C. Chen, Y. Yao, A. Drira, A. Koschan, and M. Abidi. 2009. Cooperative mapping of multiple PTZ cameras in automated surveillance systems. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 1078--1084
[13]
C. H. Chen, Y. Yao, D. Page, and B. Abidi. 2008. Heterogeneous fusion of omnidirectional and PTZ cameras for multiple object tracking. IEEE Trans. Circuits Syst. Video Technol. 18, 8, 1052--1063.
[14]
F. Dornaika and J. H. Elder. 2012. Image registration for foveated panoramic sensing. ACM Trans. Multimedia Comput. Commun. Appl. 8, 2, 1--20.
[15]
J. H Elder, F. Dornaika, Y. Hou, and R. Goldstein. 2005. Attentive Wide-Field Sensing for Visual Telepresence and Surveillance. Academic Press. Elsevier, San Diego, CA.
[16]
J. H. Elder, S. J. Prince, Y. Hou, M. Sizintsev, and E. Olevskiy. 2007. Pre-attentive and attentive detection of humans in wide-field scenes. Int. J. Comput. Vis. 72, 1, 47--66.
[17]
A. Ess, B. Leibe, K. Schindler, and L. Van Gool. 2008. A mobile vision system for robust multi-person tracking. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 1--8.
[18]
N. Gracias, M. Mahoor, S. Negahdaripour, and A. Gleason. 2009. Fast image blending using watersheds and graph cuts. Image Vis. Comput. 27, 5, 597--607.
[19]
T. T. Hu, Y. W. Chia, L. W. Chan, Y. P. Hung, and J. Hsu. 2008. im-Top: An interactive multi- resolution tabletop system accommodating to multi-resolution human vision. 2008. In Proceedings of the 3rd IEEE International Workshop on Horizontal Interactive Human Computer Systems. 177--180.
[20]
X. Kang, G. Ogunmakin, L. Yue, P. A. Vela, and W. Yongtian. 2011. PTZ camera-based adaptive panoramic and multi-layered background model. In Proceedings of the 18th IEEE International Conference on Image Processing (ICIP). 2949--2952.
[21]
X. Kang, L. Yue, O. Gbolabo, C. Jing, and Z. Jiangen. 2013. Panoramic Gaussian Mixture Model and large-scale range background subtraction method for PTZ camera-based surveillance systems. Mach. Vis. Appl. 24, 3, 477--492.
[22]
K. Kim, T. H. Chalidabhongse, D. Harwood, and L. Davis. 2005. Real-time foreground-background segmentation using codebook model. Real-Time Imaging. 11, 3, 172--185.
[23]
M. Lalonde, S. Foucher, L. Gagnon, E. Pronovost, M. Derenne, and A. Janelle. 2007. A system to automatically track humans and vehicles with a PTZ camera. In Proceedings of SPIE 6575, Visual Information Processing XVI.
[24]
D. G. Lowe. 1999. Object recognition from local scale-invariant features. In Proceedings of the 7th IEEE International Conference on Computer Vision (ICCV). 1150--1157.
[25]
L. Marchesotti, L. Marcenaro, and C. Regazzoni. 2003. Dual camera system for face detection in unconstrained environments. In Proceedings of the IEEE International Conference on Image Processing (ICIP). 681--684.
[26]
A. Mian. 2008. Realtime face detection and tracking using a single Pan, Tilt, Zoom camera. In Proceedings of the 23rd International Conference on Image and Vision Computing New Zealand (IVCNZ). 1--6.
[27]
C. Micheloni, G. Foresti, and L. Snidaro. 2005. A network of co-operative cameras for visual surveillance. IEE Proc. Vis. Image Signal Proc. 152, 2, 205--212.
[28]
C. Micheloni, B. Rinner, and G. L. Foresti. 2010. Video analysis in pan-tilt-zoom camera networks. IEEE Signal Proc. Mag. 27, 5, 78--90.
[29]
C. Micheloni, E. Salvador, F. Bigaran, and G. L. Foresti. 2005. An integrated surveillance system for outdoor security. In Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS). 480--485.
[30]
P. Natarajan, T. N. Hoang, K. H. Low, and M. Kankanhalli. 2012. Decision-theoretic approach to maximizing observation of multiple targets in multi-camera surveillance. In Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems (AAMS). 155--162.
[31]
P. Natarajan, T. N. Hoang, K. H. Low, and M. Kankanhalli. 2012. Decision-theoretic coordination and control for active multi-camera surveillance in uncertain, partially observable environments. In Proceedings of the Sixth IEEE International Conference on Distributed Smart Cameras (ICDSC), 1--6.
[32]
P. Pérez, M. Gangnet, and A. Blake. 2003. Poisson image editing. ACM Trans. Graph. 22, 3, 313--318.
[33]
PENPOWER 2012. TrackIN iDVR, Auto PTZ Tracking System. http://www.penpower.com.hk/product.asp?sn=61.
[34]
C. Plaisant, D. Carr, and B. Shneiderman. 1995. Image-browser taxonomy and guidelines for designers. IEEE Softw. 12, 2, 21--32.
[35]
S. Prince, J. H. Elder, Y. Hou, and M. Sizintsev. 2005. Pre-attentive face detection for foveated wide-field surveillance. In Proceedings of the IEEE Workshop on Applications on Computer Vision (WACV). 439--446.
[36]
W. Qing, C. Feng, X. Wenli, and Y. Ming-Hsuan. 2012. Object tracking via partial least squares analysis. IEEE Trans. Image Process. 21, 10, 4454--4465.
[37]
M. Reale, T. Hung, and L. Yin. 2010. Pointing with the eyes: Gaze estimation using a static/active camera system and 3d iris disk model. In Proceedings of the IEEE International Conference on Multimedia and Expo (ICME). 280--285.
[38]
W. Ruiping, S. Shiguang, C. Xilin, D. Qionghai, and G. Wen. 2012. Manifold-manifold distance and its application to face recognition with image sets. IEEE Trans. Image Proc. 21, 10, 4466--4479.
[39]
G. Sansoni, M. Carocci, and R. Rodella. 1999. Three-dimensional vision based on a combination of gray-code and phase-shift light projection: Analysis and compensation of the systematic errors. Appl. Optics. 38, 31, 6565--6573.
[40]
V. K. Singh and P. K. Atrey. 2005. Coopetitive visual surveillance using model predictive control. In Proceedings of the 3rd ACM International Workshop on Video Surveillance and Sensor Networks. 149--158.
[41]
V. K. Singh, P. K. Atrey, and M. S. Kankanhalli. 2008. Coopetitive multi-camera surveillance using model predictive control. Mach. Vis. Appl. 19, 5--6, 375--393.
[42]
N. Sinhas and M. Pollefeys. 2006. Pan-tilt-zoom camera calibration and high-resolution mosaic generation. Comput. Vis. Image Understand. 103, 3, 170--183
[43]
O. G. Staadt, B. A. Ahlborn, O. Kreylos, and B. Hamann. 2006. A foveal inset for large display environments. In Proceedings of the ACM International Conference on Virtual Reality Continuum and its Applications (VRCIA). 281--288.
[44]
C. Stauffer and W. E. L. Grimson. 1999. Adaptive background mixture models for real-time tracking. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR).
[45]
C. Stauffer and W. E. L. Grimson. 2000. Learning patterns of activity using real-time tracking. IEEE Trans. Pattern Anal. Mach. Intell. 22, 8, 747--757.
[46]
R. Szeliski. 2004. Image alignment and stitching: A tutorial, Tech. Rep., MSR-TR-2004--2092.
[47]
Z. Tao and R. Nevatia. 2002. Stochastic human segmentation from a static camera. In Proceedings of the Workshop on Motion and Video Computing. 9--14.
[48]
Z. Tao and R. Nevatia. 2003. Bayesian human segmentation in crowded situations. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR). 459--466.
[49]
P. Viola and M. Jones. 2001. Robust real-time object detection. Int. J. Comput. Vis. 4, 34--47.
[50]
X. Wang, T. X. Han, and S. Yan. 2009. An HOG-LBP human detector with partial occlusion handling. In Proceedings of the IEEE 12th International Conference on Computer Vision (ICCV). 32--39.
[51]
F. W. Wheeler, R. L. Weiss, and P. H. Tu. 2010. Face recognition at a distance system for surveillance applications. In Proceedings of the 4th IEEE International Conference on Biometrics: Theory Applications and Systems (BTAS). 1--8.
[52]
Y. Ye, J. K. Tsotsos, E. Harley, and K. Bennet. 2000. Tracking a person with pre-recorded image database and a pan, tilt, and zoom camera. Mach. Vis. Appl. 12, 1, 32--43.
[53]
C. Zhang, Z. Liu, Z. Zhang, and Q. Zhao. 2008. Semantic saliency driven camera control for personal remote collaboration. In Proceedings of the IEEE 10th Workshop on Multimedia Signal Processing. 28--33.
[54]
W. Zhao, R. Chellappa, P. J. Phillips, and A. Rosenfeld. 2003. Face recognition: A literature survey. ACM Comput. Surv. 35, 4, 399--458.
[55]
X. Zhou, R. T. Collins, T. Kanade, and P. Metes. 2003. A master-slave system to acquire biometric imagery of humans at distance. In Proceedings of the Ist ACM SIGMM International Workshop on Video Surveillance. 113--120.

Cited By

View all
  • (2025)Visible-Infrared Image Alignment for UAVs: Benchmark and New BaselineIEEE Transactions on Geoscience and Remote Sensing10.1109/TGRS.2025.352863463(1-14)Online publication date: 2025
  • (2025)Virtual ecological landscape design of theme parks based on entertainment robots and VR devicesEntertainment Computing10.1016/j.entcom.2024.10081252(100812)Online publication date: Jan-2025
  • (2020)Foveation Pipeline for 360° Video-Based TelemedicineSensors10.3390/s2008226420:8(2264)Online publication date: 16-Apr-2020
  • Show More Cited By

Index Terms

  1. Large-Area, Multilayered, and High-Resolution Visual Monitoring Using a Dual-Camera System

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Transactions on Multimedia Computing, Communications, and Applications
    ACM Transactions on Multimedia Computing, Communications, and Applications  Volume 11, Issue 2
    December 2014
    197 pages
    ISSN:1551-6857
    EISSN:1551-6865
    DOI:10.1145/2716635
    Issue’s Table of Contents
    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]

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 07 January 2015
    Accepted: 01 June 2014
    Revised: 01 November 2013
    Received: 01 July 2013
    Published in TOMM Volume 11, Issue 2

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. PTZ camera
    2. and high-resolution system
    3. dual-camera system
    4. large-area
    5. multilayered
    6. visual monitoring
    7. wide-angle fixed camera

    Qualifiers

    • Research-article
    • Research
    • Refereed

    Funding Sources

    • Excellent Research Projects of National Taiwan University

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)15
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 03 Mar 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2025)Visible-Infrared Image Alignment for UAVs: Benchmark and New BaselineIEEE Transactions on Geoscience and Remote Sensing10.1109/TGRS.2025.352863463(1-14)Online publication date: 2025
    • (2025)Virtual ecological landscape design of theme parks based on entertainment robots and VR devicesEntertainment Computing10.1016/j.entcom.2024.10081252(100812)Online publication date: Jan-2025
    • (2020)Foveation Pipeline for 360° Video-Based TelemedicineSensors10.3390/s2008226420:8(2264)Online publication date: 16-Apr-2020
    • (2019)A Dual-Camera Surveillance Video Summarization Generating Strategy for Multi-Target CapturingProceedings of the 3rd International Conference on Video and Image Processing10.1145/3376067.3376071(121-125)Online publication date: 20-Dec-2019
    • (2019)RTMCHMultimedia Tools and Applications10.1007/s11042-018-6480-978:6(7803-7818)Online publication date: 1-Mar-2019
    • (2018)A location and mobility independent scheme to quantify the neighbourhood stability of a node in mobile sensor networksInternational Journal of Mobile Network Design and Innovation10.5555/3272206.32722128:2(111-125)Online publication date: 1-Jan-2018
    • (2018)A location and mobility independent scheme to quantify the neighbourhood stability of a node in mobile sensor networksInternational Journal of Mobile Network Design and Innovation10.5555/3272193.32721998:2(111-125)Online publication date: 1-Jan-2018
    • (2018)A location and mobility independent scheme to quantify the neighbourhood stability of a node in mobile sensor networksInternational Journal of Mobile Network Design and Innovation10.5555/3272186.32721928:2(111-125)Online publication date: 1-Jan-2018

    View Options

    Login options

    Full Access

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media