WrenGA.hpp

/****************************************************************************
*                                                                             
*   This program is free software: you can redistribute it and/or modify     
*    it under the terms of the GNU General Public License as published by     
*    the Free Software Foundation, either version 3 of the License, or        
*    (at your option) any later version.                                      
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*    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the            
*    GNU General Public License for more details.                             
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*    You should have received a copy of the GNU General Public License        
*    along with this program. If not, see <http://www.gnu.org/licenses/>.     
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******************************************************************************/

/****************************************************************************
*
* WrenGA.hpp
*
* Purpose: Implementation of the running Gaussian average background 
*		  		 subtraction algorithm described in:
*	  			 "Pfinder: real-time tracking of the human body"
* 						by C. Wren et al (1997)
*
* Author: Donovan Parks, September 2007
*
* Please note that this is not an implementation of Pfinder. It implements
* a simple background subtraction algorithm where each pixel is represented
* by a single Gaussian and update using a simple weighting function.

Example:
		Algorithms::BackgroundSubtraction::WrenParams params;
		params.SetFrameSize(width, height);
		params.LowThreshold() = 3.5f*3.5f;
		params.HighThreshold() = 2*params.LowThreshold();	// Note: high threshold is used by post-processing 
		params.Alpha() = 0.005f;
		params.LearningFrames() = 30;

		Algorithms::BackgroundSubtraction::WrenGA bgs;
		bgs.Initalize(params);
******************************************************************************/

#ifndef WREN_GA_H
#define WREN_GA_H

#include "Bgs.hpp"

namespace Algorithms
{
namespace BackgroundSubtraction
{

// --- Parameters used by the Mean BGS algorithm ---
class WrenParams : public BgsParams
{
public:
	float &LowThreshold() { return m_low_threshold; }
	float &HighThreshold() { return m_high_threshold; }

	float &Alpha() { return m_alpha; }
	int &LearningFrames() { return m_learning_frames; }

private:
	// The threshold indicates the number of variances (not standard deviations) away
	// from the mean before a pixel is considered to be from the foreground.
	float m_low_threshold;
	float m_high_threshold;

	float m_alpha;
	int m_learning_frames;
};


// --- Mean BGS algorithm ---
class WrenGA : public Bgs
{
private:	
	struct GAUSSIAN
	{
		float mu[NUM_CHANNELS];
		float var[NUM_CHANNELS];
	};

public:
	WrenGA();
	~WrenGA();

	void Initalize(const BgsParams& param);

	void InitModel(const RgbImage& data);
	void Subtract(int frame_num, const RgbImage& data,  
									BwImage& low_threshold_mask, BwImage& high_threshold_mask);	
	void Update(int frame_num, const RgbImage& data,  const BwImage& update_mask);

	RgbImage* Background() { return &m_background; }

private:	
	void SubtractPixel(int r, int c, const RgbPixel& pixel, 
											unsigned char& lowThreshold, unsigned char& highThreshold);

	WrenParams m_params;

	// Initial variance for the newly generated components. 
	float m_variance;

	// dynamic array for the mixture of Gaussians
	GAUSSIAN* m_gaussian;

	RgbImage m_background;
};

};
};

#endif