High Dimensional versus Low Dimensional Chaos in MPEG-7 Feature Binding for Object Classification

  • Hanif Azhar
  • Aishy Amer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6134)


We proposed [1] a feature binding method to generate a MPEG-7 compliant feature vector, defined as C-MP7. Here, we study the excellence of C-MP7 as a feature vector, using either low- or high-dimensional chaos. With high-dimensional chaos-based C-MP7, we find, 1) the accuracy in SVM classifier improves 10% to 20%, for all classes of video objects over MPEG-7, 2) larger binary class separation among video objects in different classes, 3) vehicle objects are clustered well, which leads to above 99% accuracy for only vehicles against other objects in SVM, and 4) drifts in chaotic attractors allow the C-MP7 to include subtle variations in coefficients for video objects.


Chaos MPEG-7 Video Object Feature 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Hanif Azhar
    • 1
  • Aishy Amer
    • 1
  1. 1.Electrical and Computer EngineeringConcordia UniversityMontréalCanada

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