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PURPOSE ^

CHANNELS

SYNOPSIS ^

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DESCRIPTION ^

 CHANNELS
 See also

 Fast channel feature computation code based on the papers:
  [1] P. Dollár, Z. Tu, P. Perona and S. Belongie
   "Integral Channel Features", BMVC 2009.
  [2] P. Dollár, S. Belongie and P. Perona
   "The Fastest Pedestrian Detector in the West," BMVC 2010.
  [3] P. Dollár, R. Appel and W. Kienzle
   "Crosstalk Cascades for Frame-Rate Pedestrian Detection," ECCV 2012.
 Please cite a subset of the above papers if you end up using the code.
 Code written and maintained by Piotr Dollar and Ron Appel.

 Channels:
   chnsCompute  - Compute channel features at a single scale given an input image.
   chnsPyramid  - Compute channel feature pyramid given an input image.
   chnsScaling  - Compute lambdas for channel power law scaling.

 Constant time image smoothing:
   convBox      - Extremely fast 2D image convolution with a box filter.
   convMax      - Extremely fast 2D image convolution with a max filter.
   convTri      - Extremely fast 2D image convolution with a triangle filter.

 Gradients and gradient histograms:
   gradient2    - Compute numerical gradients along x and y directions.
   gradientHist - Compute oriented gradient histograms.
   gradientMag  - Compute gradient magnitude and orientation at each image location.
   hog          - Efficiently compute histogram of oriented gradient (HOG) features.
   hogDraw      - Create visualization of hog descriptor.

 Miscellaneous:
   imPad        - Pad an image along its four boundaries.
   imResample   - Fast bilinear image downsampling/upsampling.
   rgbConvert   - Convert RGB image to other color spaces (highly optimized).

CROSS-REFERENCE INFORMATION ^

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