org.openimaj.image.feature.dense.gradient.binning

Class FlexibleHOGStrategy

java.lang.Object

org.openimaj.image.feature.dense.gradient.binning.FlexibleHOGStrategy

All Implemented Interfaces:

SpatialBinningStrategy

public class FlexibleHOGStrategy
extends Object
implements SpatialBinningStrategy

A SpatialBinningStrategy very much like the FixedHOGStrategy, but with flexibly sized cells that grow/shrink such that the number of cells in any given window is constant. Coupled with a GradientOrientationHistogramExtractor, this provides a way to efficiently extract the HOG descriptor of any rectangular window.

Author:

Jonathon Hare (jsh2@ecs.soton.ac.uk)

Constructor Summary

Constructors

Constructor and Description
FlexibleHOGStrategy(int numCellsX, int numCellsY, int cellsPerBlock) Construct with the given number of cells per window (or image).
FlexibleHOGStrategy(int numCellsX, int numCellsY, int cellsPerBlock, FixedHOGStrategy.BlockNormalisation norm) Construct with the given number of cells per window (or image).
FlexibleHOGStrategy(int numCellsX, int numCellsY, int cellsPerBlock, int blockStep, FixedHOGStrategy.BlockNormalisation norm) Construct with the given number of cells per window (or image).
FlexibleHOGStrategy(int numCellsX, int numCellsY, int cellsPerBlockX, int cellsPerBlockY, int blockStepX, int blockStepY, FixedHOGStrategy.BlockNormalisation norm) Construct with the given number of cells per window (or image).

Method Summary

Modifier and Type	Method and Description
Histogram	extract(WindowedHistogramExtractor binnedData, Rectangle region, Histogram output) Extract a histogram describing image content in the given region using the given WindowedHistogramExtractor to extract (sub) histograms from which to build the output.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

FlexibleHOGStrategy

public FlexibleHOGStrategy(int numCellsX,
                           int numCellsY,
                           int cellsPerBlock)

Construct with the given number of cells per window (or image). Square blocks are constructed from the given number of cells in each dimension. Blocks overlap, and shift by 1 cell (i.e. overlap is cellsPerBlock - 1). FixedHOGStrategy.BlockNormalisation.L2 is used for block normalisation.

Parameters:

numCellsX - the number of cells per window in the x direction

numCellsY - the number of cells per window in the y direction

cellsPerBlock - the number of cells per block

FlexibleHOGStrategy

public FlexibleHOGStrategy(int numCellsX,
                           int numCellsY,
                           int cellsPerBlock,
                           FixedHOGStrategy.BlockNormalisation norm)

Construct with the given number of cells per window (or image). Square blocks are constructed from the given number of cells in each dimension. Blocks overlap, and shift by 1 cell (i.e. overlap is cellsPerBlock - 1).

Parameters:

numCellsX - the number of cells per window in the x direction

numCellsY - the number of cells per window in the y direction

cellsPerBlock - the number of cells per block

norm - the normalisation scheme

FlexibleHOGStrategy

public FlexibleHOGStrategy(int numCellsX,
                           int numCellsY,
                           int cellsPerBlock,
                           int blockStep,
                           FixedHOGStrategy.BlockNormalisation norm)

Construct with the given number of cells per window (or image). Square blocks are constructed from the given number of cells in each dimension.

Parameters:

numCellsX - the number of cells per window in the x direction

numCellsY - the number of cells per window in the y direction

cellsPerBlock - the number of cells per block

blockStep - the amount to shift each block in terms of cells

norm - the normalisation scheme

FlexibleHOGStrategy

public FlexibleHOGStrategy(int numCellsX,
                           int numCellsY,
                           int cellsPerBlockX,
                           int cellsPerBlockY,
                           int blockStepX,
                           int blockStepY,
                           FixedHOGStrategy.BlockNormalisation norm)

Construct with the given number of cells per window (or image). Rectangular blocks are constructed from the given number of cells in each dimension.

Parameters:

numCellsX - the number of cells per window in the x direction

numCellsY - the number of cells per window in the y direction

cellsPerBlockX - the number of cells per block in the x direction

cellsPerBlockY - the number of cells per block in the y direction

blockStepX - the amount to shift each block in terms of cells in the x direction

blockStepY - the amount to shift each block in terms of cells in the y direction

norm - the normalisation scheme

Method Detail

extract

public Histogram extract(WindowedHistogramExtractor binnedData,
                         Rectangle region,
                         Histogram output)

Description copied from interface: SpatialBinningStrategy

Extract a histogram describing image content in the given region using the given WindowedHistogramExtractor to extract (sub) histograms from which to build the output.

For efficiency, this method allows the output histogram to be specified as an input. This means that implementors of this interface can attempt to fill the output histogram rather than creating a new instance (although care should be taken to ensure that the porivded output histogram is the correct size and not null).

Users of SpatialBinningStrategys should use the following style for maximum efficiency:

 Histogram h = null;
 ...
 for (Rectangle region : lots_of_regions)
        h = strategy.extract(binnedData, region, h);
 

Specified by:

extract in interface SpatialBinningStrategy

Parameters:

binnedData - the WindowedHistogramExtractor to extract sub-histograms from

region - the region to extract from

output - the output histogram to fill (can be null)

Returns:

the extracted histogram (preferably output)