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A smart method for tracking of moving objects on production line

Published: 08 December 2008 Publication History

Abstract

A decision-making analysis method was described for tracking of moving objects in automation product line. Based on coordinates of moving objects in image sequence, combined with the displacement information provided by servo controlled conveyer, this method solved the problem of targets' repeated identification and missing. The dependable targets' localization information was required and provided to the packing robot.

References

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Galata, A., Johnson, N., and Hogg, D. 2001. Learning variable length markov models of behavior. Computer Vision and Image Understanding 81, 3, 398--413.
[3]
Stauffer, C. and Grimson, W. 1999. Adaptive background mixture models for real-time tracking. The Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition 2, 246--252.
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Toyama, K., Krumm, J., and Brumitt, B. 1999. Wallflower: Principles and practice of background maintenance. The Proceedings of the IEEE International Conference on Computer Vision 1, 255--261.
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Haritaoglu, I., Harwood, D., and Davis, L. S. 2000. W4: real time surveillance of people and their activities. IEEE Transactions on Pattern Analysis and Machine Intelligence 22, 8, 809--830.
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Stenger, B., Ramesh, V., and Paragios, N. 2001. Topology free hidden markov models: Application to background modeling. The Proceedings of the IEEE International Conference on Computer Vision, 1, 294--301.
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Elgammal, A., Duraiswami, R., and Harwood, D. 2002. Background and foreground modeling using nonparametric kernel density estimation for visual surveillance. The Proceedings of the IEEE, 90, 7, 1151--1163.

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  1. A smart method for tracking of moving objects on production line

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    cover image ACM Conferences
    VRCAI '08: Proceedings of The 7th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry
    December 2008
    223 pages
    ISBN:9781605583358
    DOI:10.1145/1477862
    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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    New York, NY, United States

    Publication History

    Published: 08 December 2008

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    Author Tags

    1. CCD camera
    2. machine vision
    3. moving object tracking
    4. packing robot

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    Overall Acceptance Rate 51 of 107 submissions, 48%

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