001/**
002 * Copyright (c) 2011, The University of Southampton and the individual contributors.
003 * All rights reserved.
004 *
005 * Redistribution and use in source and binary forms, with or without modification,
006 * are permitted provided that the following conditions are met:
007 *
008 *   *  Redistributions of source code must retain the above copyright notice,
009 *      this list of conditions and the following disclaimer.
010 *
011 *   *  Redistributions in binary form must reproduce the above copyright notice,
012 *      this list of conditions and the following disclaimer in the documentation
013 *      and/or other materials provided with the distribution.
014 *
015 *   *  Neither the name of the University of Southampton nor the names of its
016 *      contributors may be used to endorse or promote products derived from this
017 *      software without specific prior written permission.
018 *
019 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
020 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
021 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
022 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
023 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
024 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
025 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
026 * ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
027 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
028 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
029 */
030package org.openimaj.feature.local.matcher;
031
032import java.util.ArrayList;
033import java.util.List;
034
035import org.openimaj.image.feature.local.keypoints.Keypoint;
036import org.openimaj.knn.approximate.ByteNearestNeighboursKDTree;
037import org.openimaj.util.pair.Pair;
038
039/**
040 * 
041 * Uses a ByteKDTree to estimate approximate nearest neighbours more
042 * efficiently.
043 * 
044 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
045 * @author Sina Samangooei (ss@ecs.soton.ac.uk)
046 * 
047 * @param <T>
048 */
049public class FastEuclideanKeypointMatcher<T extends Keypoint> implements LocalFeatureMatcher<T> {
050        private ByteNearestNeighboursKDTree modelKeypointsKNN;
051        private int threshold;
052        protected List<Pair<T>> matches;
053        private List<T> modelKeypoints;
054
055        /**
056         * @param threshold
057         *            threshold for determining matching keypoints
058         */
059        public FastEuclideanKeypointMatcher(int threshold) {
060                this.threshold = threshold;
061        }
062
063        @Override
064        public void setModelFeatures(List<T> modelkeys) {
065                modelKeypoints = modelkeys;
066
067                final byte[][] data = new byte[modelkeys.size()][];
068                for (int i = 0; i < modelkeys.size(); i++)
069                        data[i] = modelkeys.get(i).ivec;
070
071                modelKeypointsKNN = new ByteNearestNeighboursKDTree(data, 8, 768);
072        }
073
074        @Override
075        public boolean findMatches(List<T> keys1) {
076                matches = new ArrayList<Pair<T>>();
077
078                final byte[][] data = new byte[keys1.size()][];
079                for (int i = 0; i < keys1.size(); i++)
080                        data[i] = keys1.get(i).ivec;
081
082                final int[] argmins = new int[keys1.size()];
083                final float[] mins = new float[keys1.size()];
084                modelKeypointsKNN.searchNN(data, argmins, mins);
085
086                for (int i = 0; i < keys1.size(); i++) {
087                        final float distsq = mins[i];
088
089                        if (distsq < threshold) {
090                                matches.add(new Pair<T>(keys1.get(i), modelKeypoints.get(argmins[i])));
091                        }
092                }
093
094                return true;
095        }
096
097        @Override
098        public List<Pair<T>> getMatches() {
099                return this.matches;
100        }
101
102        /**
103         * Set the matching threshold
104         * 
105         * @param threshold
106         *            the threshold
107         */
108        public void setThreshold(int threshold) {
109                this.threshold = threshold;
110        }
111}