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spx_svm's Introduction

SPX_SVM

SVM classification on Superpixel.

Input : TrainImage, ROI and TestImage

Output : Superpixel of TestImage classified by SVM, separating foreground superpixels from background superpixels

Detail :

  1. Training
  • Draw ROI on TrainImage to select Foreground region
  • Apply grabCut (from openCV) to have coarse fgnd/bgnd subtraction
  • Oversegment TrainImage with SLIC to get the superpixels
  • Select foreground superpixel samples if #pixel_fgnd>threshold inside that superpixel
  • Select background superpixel samples in area around ROI
  • Do SVM training with those samples
  1. Test :
  • Segment TestImage in Superpixel
  • Extract feature from each Superpixel
  • Classify each Superpixel with SVM

Note : Different settings are available

  • Color Space : BGR, HSV, Lab
  • Feature : MEAN_COLOR, HISTOGRAM3D
  • SVM Types : ONE CLASS , TWO CLASS
  • SVM Kernel : LINEAR, RBF
  • SLIC parameter : size/number of Superpixel, compactness
  • Background ROI size : fullFrame -> all the superpixel out of ROI, or scaleROI -> BROI = X*ROI-ROI

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