• DocumentCode
    888310
  • Title

    Multiple light source detection

  • Author

    Bouganis, Christos-Savvas ; Brookes, Mike

  • Author_Institution
    EEE Dept., Imperial Coll., London, UK
  • Volume
    26
  • Issue
    4
  • fYear
    2004
  • fDate
    4/1/2004 12:00:00 AM
  • Firstpage
    509
  • Lastpage
    514
  • Abstract
    This paper presents the V2R algorithm, a novel method for multiple light source detection using a Lambertian sphere as a calibration object. The algorithm segments the image of the sphere into regions that are each illuminated by a single virtual light and subtracts the virtual lights of adjacent regions to estimate the light source vectors. The algorithm uses all pixels within a region to form a robust estimate of the corresponding virtual light. The circumstances under which the light source detection problem lacks a unique solution are discussed in detail and the way in which the V2R algorithm resolves the ambiguity is explained. The V2R algorithm includes novel procedures for identifying the critical lines that bound the regions, for estimating the light source vectors, and for identifying opposite light pairs. Experiments are performed on synthetic and real images and the performance of the V2R algorithm is compared to that of a recent algorithm from the literature. The experimental results demonstrate that the proposed algorithm is robust and that it gives substantially improved accuracy.
  • Keywords
    computer vision; image recognition; image segmentation; light sources; Lambertian sphere; V2R algorithm; calibration object; light source vectors; multiple light source detection; real images; synthetic images; virtual light; Calibration; Cameras; H infinity control; Image generation; Image segmentation; Light sources; Object detection; Robustness; Shape; Testing; Algorithms; Artificial Intelligence; Computer Graphics; Computer Simulation; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Information Storage and Retrieval; Lighting; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated; Photometry; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Subtraction Technique;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/TPAMI.2004.1265865
  • Filename
    1265865