Qualitative Representations for Recognition

  • Pawan Sinha
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2525)


The success of any object recognition system, whether biological or artificial, lies in using appropriate representation schemes. The schemes should efficiently encode object concepts while being tolerant to appearance variations induced by changes in viewing geometry and illumination. Here, we present a biologically plausible representation scheme wherein objects are encoded as sets of qualitative image measurements. Our emphasis on the use of qualitative measurements renders the representations stable in the presence of sensor noise and significant changes in object appearance. We develop our ideas in the context of the task of face-detection under varying illumination. Our approach uses qualitative photometric measurements to construct a face signature (‘ratiotemplate’) that is largely invariant to illumination changes.


Receptive Field Face Image Face Detection Image Patch Qualitative Representation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Pawan Sinha
    • 1
  1. 1.Department of Brain and Cognitive SciencesMassachusetts Institute of TechnologyCambridge

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