Contents

 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.
  [4] P. Dollár, R. Appel, S. Belongie and P. Perona
   "Fast Feature Pyramids for Object Detection", PAMI 2014.
 Please cite a subset of the above papers if you end up using the code.
 The PAMI 2014 paper has the most thorough and up to date descriptions.
 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.
   fhog         - Efficiently compute Felzenszwalb's HOG (FHOG) features.

 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).