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STSIM-C Texture Similarity

Experimental Procedure

  1. STSIM vector extraction
  2. Compute covariance matrix
  3. Approximate Cross Validation
    • Compute cluster center or set example for retrieval
    • Measure Precision@1 and RoC

Experimental Settings:

  • Global or Intraclass covariance matrix calculation
  • Color or Grayscale features

Datasets:

  • CuReT: Fewer classes, many examples per class
    • Represent class with many exemplars
    • Tests under variation of lighting and viewing conditions
  • Identical: Same texture, perceptually identical
  • ViSiProg: Different classes; Perceptually similar
  • Distortions: Single image with applied distortion translation, rotations, scaling, etc.

Differences from previous work:

  • Previous work would have made assumptions among feature correlation
  • Similarity is order invariant
  • 1-,2-Color improves accuracym; Minimal gains for 4-color