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Localization and mapping of surveillance cameras in city map

Published: 26 October 2008 Publication History

Abstract

Many large cities have installed surveillance cameras to monitor human activities for security purposes. An important surveillance application is to track the motion of an object of interest, e.g., a car or a human, using one or more cameras, and plot the motion path in a city map. To achieve this goal, it is necessary to localize the cameras in the city map and to determine the correspondence mappings between the positions in the city map and the camera views. Since the view of the city map is roughly orthogonal to the camera views, there are very few common features between the two views for a computer vision algorithm to correctly identify corresponding points automatically. This paper proposes a method for camera localization and position mapping that requires minimum user inputs. Given approximate corresponding points between the city map and a camera view identified by a user, the method computes the orientation and position of the camera in the city map, and determines the mapping between the positions in the city map and the camera view. Both quantitative tests and practical application test have been performed. It can obtain the best-fit solutions even though the user-specified correspondence is inaccurate. The performance of the method is assessed in both quantitative tests and practical application. Quantitative test results show that the method is accurate and robust in camera localization and position mapping. Application test results are very encouraging, showing the usefulness of the method in real applications.

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Cited By

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  • (2023)Crowd Density Estimation and Mapping Method Based on Surveillance Video and GISISPRS International Journal of Geo-Information10.3390/ijgi1202005612:2(56)Online publication date: 8-Feb-2023
  • (2022)Sensing the Sensor: Estimating Camera Properties with Minimal InformationACM Transactions on Sensor Networks10.1145/350839318:2(1-26)Online publication date: 4-Feb-2022
  • (2017)Visual Self-localization via Inferring View-to-Map CorrespondencesProceedings of the Workshop on Visual Analysis in Smart and Connected Communities10.1145/3132734.3132740(33-39)Online publication date: 23-Oct-2017
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    cover image ACM Conferences
    MM '08: Proceedings of the 16th ACM international conference on Multimedia
    October 2008
    1206 pages
    ISBN:9781605583037
    DOI:10.1145/1459359
    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]

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    Publication History

    Published: 26 October 2008

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    Author Tags

    1. camera localization
    2. position mapping
    3. surveillance

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    MM08
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    MM08: ACM Multimedia Conference 2008
    October 26 - 31, 2008
    British Columbia, Vancouver, Canada

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    Cited By

    View all
    • (2023)Crowd Density Estimation and Mapping Method Based on Surveillance Video and GISISPRS International Journal of Geo-Information10.3390/ijgi1202005612:2(56)Online publication date: 8-Feb-2023
    • (2022)Sensing the Sensor: Estimating Camera Properties with Minimal InformationACM Transactions on Sensor Networks10.1145/350839318:2(1-26)Online publication date: 4-Feb-2022
    • (2017)Visual Self-localization via Inferring View-to-Map CorrespondencesProceedings of the Workshop on Visual Analysis in Smart and Connected Communities10.1145/3132734.3132740(33-39)Online publication date: 23-Oct-2017
    • (2014)Camera Localization UsingTrajectories and MapsIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2013.24336:4(684-697)Online publication date: 1-Apr-2014
    • (2012)$k$-Angle Object Coverage Problem in a Wireless Sensor NetworkIEEE Sensors Journal10.1109/JSEN.2012.219805412:12(3408-3416)Online publication date: Dec-2012
    • (2009)Optimization of image mapping & camera coverage efficiency for continuous location and tracking2009 IEEE 9th Malaysia International Conference on Communications (MICC)10.1109/MICC.2009.5431397(742-747)Online publication date: Dec-2009
    • (2009)A portable geo-aware visual surveillance system for vehicles2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops10.1109/ICCVW.2009.5457463(1267-1274)Online publication date: Sep-2009

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