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Träfflista för sökning "WFRF:(Narayanan S) srt2:(2005-2009)"

Search: WFRF:(Narayanan S) > (2005-2009)

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1.
  • Abazov, V. M., et al. (author)
  • The upgraded DO detector
  • 2006
  • In: Nuclear Instruments and Methods in Physics Research Section A. - : Elsevier BV. - 0168-9002 .- 1872-9576. ; 565:2, s. 463-537
  • Journal article (peer-reviewed)abstract
    • The DO experiment enjoyed a very successful data-collection run at the Fermilab Tevatron collider between 1992 and 1996. Since then, the detector has been upgraded to take advantage of improvements to the Tevatron and to enhance its physics capabilities. We describe the new elements of the detector, including the silicon microstrip tracker, central fiber tracker, solenoidal magnet, preshower detectors, forward muon detector, and forward proton detector. The uranium/liquid -argon calorimeters and central muon detector, remaining from Run 1, are discussed briefly. We also present the associated electronics, triggering, and data acquisition systems, along with the design and implementation of software specific to DO.
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2.
  • Kristensen, Fredrik, et al. (author)
  • Background segmentation beyond RGB
  • 2006
  • In: Computer Vision – ACCV 2006 / Lecture Notes in Computer Science. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 1611-3349 .- 0302-9743. - 9783540312444 ; 3852, s. 602-612
  • Conference paper (peer-reviewed)abstract
    • To efficiently classify and track video objects in a surveillance application, it is essential to reduce the amount of streaming data. One solution is to segment the video into background, i.e. stationary objects, and foreground, i.e. moving objects, and then discard the background. One such motion segmentation algorithm that has proven reliable is the Stauffer and Crimson algorithm. This paper investigates how different color spaces affect the segmentation result in terms of noise and shadow sensitivity. Shadows are especially problematic since they not only distort shape but can also result in falsely connected objects that will complicate tracking and classification. Therefore, a new decision kernel for the segmentation algorithm is presented. This kernel alters the probability of foreground detection to reduce shadows and to increase the chance of correct segmentation for objects with a skin tone color, e.g. faces.
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  • Result 1-2 of 2

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