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.MBFImage; 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 MBFImage} 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 MBFMeanVarianceField 047extends 048VideoAnalyser<MBFImage> 049{ 050 private MBFImage mean; 051 private MBFImage m2; 052 private int n; 053 054 @Override 055 public void analyseFrame(MBFImage frame) { 056 final int width = frame.getWidth(); 057 final int height = frame.getHeight(); 058 final int nBands = frame.numBands(); 059 060 if (mean == null || mean.getWidth() != width || mean.getHeight() != height || mean.numBands() != nBands) { 061 n = 0; 062 mean = new MBFImage(width, height, nBands); 063 m2 = new MBFImage(width, height, nBands); 064 } 065 066 for (int b = 0; b < nBands; b++) { 067 final float[][] mp = mean.getBand(b).pixels; 068 final float[][] m2p = m2.getBand(b).pixels; 069 final float[][] fp = frame.getBand(b).pixels; 070 for (int y = 0; y < height; y++) { 071 for (int x = 0; x < width; x++) { 072 final float v = fp[y][x]; 073 final float delta = v - mp[y][x]; 074 075 n++; 076 mp[y][x] = mp[y][x] + delta / n; 077 m2p[y][x] = m2p[y][x] + delta * (v - mp[y][x]); 078 } 079 } 080 } 081 } 082 083 /** 084 * Reset the accumulated field data. 085 * 086 * @see org.openimaj.video.processor.VideoProcessor#reset() 087 */ 088 @Override 089 public void reset() { 090 this.mean = null; 091 this.m2 = null; 092 } 093 094 /** 095 * Get the mean field of all the frames that have been analysed so far. 096 * 097 * @return the mean field. 098 */ 099 public MBFImage getMean() { 100 return mean; 101 } 102 103 /** 104 * Get the variance field of all the frames that have been analysed so far. 105 * 106 * @return the variance field. 107 */ 108 public MBFImage getVariance() { 109 if (m2 == null) 110 return null; 111 112 return m2.divide((float) (n - 1)); 113 } 114}