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Video Surveillance

Object Detection under Varying Illumination

The goal is to detect moving objects under background changes. We are researching about background modeling which is effective for illumination changes and motion changes such as movements of trees and water surface. To realize low cost and high performance background model, we are also researching about a new framework for modeling scene changes and for selecting the most effective model for each scene.
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Journals (Peer-reviewed)

  1. Satoshi Yoshinaga, Atsushi Shimada, Hajime Nagahara, Rin-ichiro Taniguchi
    Statistical Local Difference Pattern for Background Modeling
    IPSJ Transactions on Computer Vision and Applications, Vol.3, pp.198-210, 2011.12
    BibTeX
  2. Atsushi Shimada, Satoshi Yoshinaga, Rin-ichiro Taniguchi
    Maintenance of Blind Background Model for Robust Object Detection
    IPSJ Transactions on Computer Vision and Applications, Vol.3, pp.148-159, 2011.12
    BibTeX

Wide-area Object Tracking

We are researching about object tracking in the wide area where many sensors are arranged distributedly, such as a shopping mall and a town.
The connection among the sensors is automatically estimated by using the tracking results in each sensor. As with the number of sensors, many computers are required for the wide area tracking.
Therefore, with the view of load balancing and accuracy enhancement, we are also researching about estimating automatically an optimal sensor assignment for each computer.
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International Conferences (Peer-reviewed)

  1. Shuhei Noda, Atsushi Shimada, Daisaku Arita, Rin-ichiro Taniguchi
    Object Tracking across Non-overlapping Views of Multiple Sensors
    Proc. of International Workshop on "Sensing Web" in conjunction with the 19th International Conference on Pattern Recognition (ICPR2008), 2008.12
    BibTeX