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.ml.classification.cascade;
031
032import org.openimaj.image.objectdetection.haar.StageTreeClassifier;
033
034public class CascadeLearner {
035        float maximumFPRPerStage;
036        float minimumDRPerStage;
037        float targetFPR;
038
039        StageTreeClassifier learn() {
040                final float overallFPR = 1.0f;
041                final float overallDR = 1.0f;
042
043                float previousFPR = overallFPR;
044                final float previousDR = overallDR;
045                for (int i = 0; overallFPR > targetFPR; i++) {
046
047                        for (int n = 0; overallFPR > maximumFPRPerStage * previousFPR; n++) {
048                                // perform adaboost step
049
050                                // evaluate on validation set (compute overallFPR and overallDR)
051
052                                // decrease current stage threshold to achieve overallDR >=
053                                // minimumDRPerStage*previousDR
054                                // (recompute overallFPR at the same time)
055                        }
056
057                        previousFPR = overallFPR;
058                }
059
060                return null;
061        }
062}