• DocumentCode
    1575163
  • Title

    Object Detection and Recognition via Deformable Illumination and Deformable Shape

  • Author

    Zhou, Qu ; Ma, L. ; Celenk, Mehmet ; Chelberg, David

  • Author_Institution
    Chrontel Inc., San Jose, CA, USA
  • fYear
    2006
  • Firstpage
    2737
  • Lastpage
    2740
  • Abstract
    Detecting and recognizing objects in unstructured environments is one of the most challenging tasks in computer vision research. We propose an innovative algorithm, called deformable illumination, to address the problem of illumination variance in natural environments. Parallel to the role of deformable shape in object recognition, deformable illumination is designed as an object detection technique. A unified framework presented here integrates both deformable illumination and deformable shape as a simultaneous scheme for object detection and recognition in unstructured environments. Experimental results show the effectiveness of deformable illumination in addressing illumination variance.
  • Keywords
    computer vision; object detection; object recognition; computer vision research; deformable illumination algorithm; deformable shape; illumination variance problem; natural environments; object detection; object recognition; unstructured environments; Active shape model; Deformable models; Image edge detection; Image segmentation; Layout; Lighting; Object detection; Object recognition; Principal component analysis; Shape measurement; Object detection; Object recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2006 IEEE International Conference on
  • Conference_Location
    Atlanta, GA
  • ISSN
    1522-4880
  • Print_ISBN
    1-4244-0480-0
  • Type

    conf

  • DOI
    10.1109/ICIP.2006.313113
  • Filename
    4107135