boofcv.factory.tracker.FactoryTrackerObjectAlgs Maven / Gradle / Ivy

Go to download
Show more of this group Show more artifacts with this name
Show all versions of recognition Show documentation
BoofCV is an open source Java library for real-time computer vision and robotics applications.
There is a newer version: 0.26
/*
 * Copyright (c) 2011-2016, Peter Abeles. All Rights Reserved.
 *
 * This file is part of BoofCV (http://boofcv.org).
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *   http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package boofcv.factory.tracker;

import boofcv.abst.filter.derivative.ImageGradient;
import boofcv.abst.tracker.ConfigCirculantTracker;
import boofcv.abst.tracker.ConfigComaniciu2003;
import boofcv.alg.interpolate.InterpolatePixelMB;
import boofcv.alg.interpolate.InterpolatePixelS;
import boofcv.alg.tracker.circulant.CirculantTracker;
import boofcv.alg.tracker.meanshift.*;
import boofcv.alg.tracker.sfot.SfotConfig;
import boofcv.alg.tracker.sfot.SparseFlowObjectTracker;
import boofcv.alg.tracker.tld.TldParameters;
import boofcv.alg.tracker.tld.TldTracker;
import boofcv.core.image.border.BorderType;
import boofcv.factory.interpolate.FactoryInterpolation;
import boofcv.struct.image.*;

/**
 * Factory for creating low level implementations of object tracking algorithms.  These algorithms allow
 * the user to specify an object in a video stream and then track it.  For a high level and user to use
 * common interface see {@link FactoryTrackerObjectQuad}
 *
 * @author Peter Abeles
 */
public class FactoryTrackerObjectAlgs {

	public static 
	TldTracker createTLD( TldParameters config ,
							   InterpolatePixelS interpolate , ImageGradient gradient ,
							   Class imageType , Class derivType ) {
		return new TldTracker(config,interpolate,gradient,imageType,derivType);
	}

	public static 
	SparseFlowObjectTracker createSparseFlow( SfotConfig config ,
												   Class imageType , Class derivType ,
												   ImageGradient gradient) {
		return new SparseFlowObjectTracker(config,imageType,derivType,gradient);
	}

	public static 
	PixelLikelihood likelihoodHueSatHistIndependent(
			double maxPixelValue , int numHistogramBins , ImageType imageType )
	{
		if( imageType.getFamily() != ImageType.Family.PLANAR)
			throw new IllegalArgumentException("Only Planar images supported currently");
		if( imageType.getNumBands() != 3 )
			throw new IllegalArgumentException("Input image type must have 3 bands.");

		if( imageType.getDataType() == ImageDataType.U8 ) {
			return (PixelLikelihood)new LikelihoodHueSatHistInd_PL_U8((int)maxPixelValue,numHistogramBins);
		} else {
			throw new RuntimeException("Band type not yet supported "+imageType.getDataType());
		}
	}

	public static 
	PixelLikelihood likelihoodHueSatHistCoupled(
			double maxPixelValue , int numHistogramBins , ImageType imageType )
	{
		if( imageType.getFamily() != ImageType.Family.PLANAR)
			throw new IllegalArgumentException("Only Planar images supported currently");
		if( imageType.getNumBands() != 3 )
			throw new IllegalArgumentException("Input image type must have 3 bands.");

		if( imageType.getDataType() == ImageDataType.U8 ) {
			return (PixelLikelihood)new LikelihoodHueSatHistCoupled_PL_U8((int)maxPixelValue,numHistogramBins);
		} else {
			throw new RuntimeException("Band type not yet supported "+imageType.getDataType());
		}
	}

	public static 
	PixelLikelihood likelihoodHistogramCoupled( double maxPixelValue , int numHistogramBins , ImageType imageType )
	{
		switch( imageType.getFamily() ) {
			case GRAY:
				if( imageType.getDataType() != ImageDataType.U8 )
					throw new IllegalArgumentException("Only U8 currently supported");
				return (PixelLikelihood)new LikelihoodHistCoupled_SB_U8((int)maxPixelValue,numHistogramBins);

			case PLANAR:
				if( imageType.getDataType() == ImageDataType.U8 ) {
					return (PixelLikelihood)new LikelihoodHistCoupled_PL_U8((int)maxPixelValue,numHistogramBins);
				} else {
					throw new RuntimeException("Band type not yet supported "+imageType.getDataType());
				}

			default:
				throw new IllegalArgumentException("Image family not yet supported.  Try Planar");
		}
	}

	public static 
	CirculantTracker circulant( ConfigCirculantTracker config , Class imageType) {
		if( config == null )
			config = new ConfigCirculantTracker();

		InterpolatePixelS interp = FactoryInterpolation.bilinearPixelS(imageType, BorderType.EXTENDED);

		return new CirculantTracker(
				config.output_sigma_factor,config.sigma,config.lambda,config.interp_factor,
				config.padding,
				config.workSpace,
				config.maxPixelValue,interp);
	}

	public static 
	TrackerMeanShiftComaniciu2003 meanShiftComaniciu2003(ConfigComaniciu2003 config, ImageType imageType ) {

		if( config == null )
			config = new ConfigComaniciu2003();

		InterpolatePixelMB interp = FactoryInterpolation.createPixelMB(0,config.maxPixelValue,
				config.interpolation, BorderType.EXTENDED,imageType);

		LocalWeightedHistogramRotRect hist =
				new LocalWeightedHistogramRotRect(config.numSamples,config.numSigmas,config.numHistogramBins,
						imageType.getNumBands(),config.maxPixelValue,interp);

		return new TrackerMeanShiftComaniciu2003(
				config.updateHistogram,config.meanShiftMaxIterations,config.meanShiftMinimumChange,
				config.scaleWeight,config.minimumSizeRatio,config.scaleChange,hist);
	}
}