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Face detection
 

Face detection

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    Face detection Face detection Presentation Transcript

    • Face detection
      Tuck N.
    • IDEF0 decomposition
    • Face detection’s approaches
      Contour images analysis
      Intensity and colors analisys
      Adaptive classifier
    • Contour images analysis
    • Face detection’s approaches
    • Face detection’s approaches
      Skin color’s cluster
    • Adaptive classifier
    • Adaptive classifier
    • AdaBoost
      AdaBoost is an algorithm for constructing a “strong” classifier as linear combination
      f(x) =αtht(x)
      of “simple” “weak” classifiers ht(x) : X -> {−1,+1}.
    • Rapid Object Detection using a Boosted Cascade of Simple Features
      Integral Images
    • Algorithm workflow
    • Classifier’s algorithm workflow
    • OWL model
      We can use OWL model to store some data, used in our application. For example, I’ve stored maximum and minimum area of faces, that should be detected. According to w3c standarts:
      <owl:Restriction>
      <owl:onPropertyrdf:resource="#minWidth" />
      <owl:minCardinalityrdf:datatype="&xsd;nonNegativeInteger">20</owl:minCardinality>
      </owl:Restriction>
      <owl:Restriction>
      <owl:onPropertyrdf:resource="#maxWidth" />
      <owl:maxCardinalityrdf:datatype="&xsd;nonNegativeInteger">300</owl:maxCardinality>
      </owl:Restriction>
    • OWL and C# interaction
      We can use standartXmlDocumentReader to parse OWL model. Also we can use LINQ to parse this model.