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.video.processing.pixels;
031
032import org.openimaj.image.FImage;
033import org.openimaj.video.analyser.VideoAnalyser;
034import org.openimaj.video.processing.shotdetector.HistogramVideoShotDetector;
035
036/**
037 * Compute the mean and variance fields from a video of {@link FImage} frames.
038 * The generated fields could be used to analyse which parts of a video are
039 * stationary or change a lot. If your video consists of multiple shots, between
040 * which there are large changes in the content, then it probably makes sense to
041 * segment the video using a {@link HistogramVideoShotDetector} and apply a new
042 * analyser to each shot independently.
043 *
044 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
045 */
046public class FMeanVarianceField
047extends
048                VideoAnalyser<FImage>
049{
050        private FImage mean;
051        private FImage m2;
052        private int n;
053
054        @Override
055        public void analyseFrame(FImage frame) {
056                final int width = frame.width;
057                final int height = frame.height;
058
059                if (mean == null || mean.width != width || mean.height != height) {
060                        n = 0;
061                        mean = new FImage(width, height);
062                        m2 = new FImage(width, height);
063                }
064
065                final float[][] mp = mean.pixels;
066                final float[][] m2p = m2.pixels;
067                final float[][] fp = frame.pixels;
068                for (int y = 0; y < height; y++) {
069                        for (int x = 0; x < width; x++) {
070                                final float v = fp[y][x];
071                                final float delta = v - mp[y][x];
072
073                                n++;
074                                mp[y][x] = mp[y][x] + delta / n;
075                                m2p[y][x] = m2p[y][x] + delta * (v - mp[y][x]);
076                        }
077                }
078        }
079
080        /**
081         * Reset the accumulated field data.
082         *
083         * @see org.openimaj.video.processor.VideoProcessor#reset()
084         */
085        @Override
086        public void reset() {
087                this.mean = null;
088                this.m2 = null;
089        }
090
091        /**
092         * Get the mean field of all the frames that have been analysed so far.
093         *
094         * @return the mean field.
095         */
096        public FImage getMean() {
097                return mean;
098        }
099
100        /**
101         * Get the variance field of all the frames that have been analysed so far.
102         *
103         * @return the variance field.
104         */
105        public FImage getVariance() {
106                if (m2 == null)
107                        return null;
108
109                return m2.divide((float) (n - 1));
110        }
111}