1 /**
2 * Copyright (c) 2011, The University of Southampton and the individual contributors.
3 * All rights reserved.
4 *
5 * Redistribution and use in source and binary forms, with or without modification,
6 * are permitted provided that the following conditions are met:
7 *
8 * * Redistributions of source code must retain the above copyright notice,
9 * this list of conditions and the following disclaimer.
10 *
11 * * Redistributions in binary form must reproduce the above copyright notice,
12 * this list of conditions and the following disclaimer in the documentation
13 * and/or other materials provided with the distribution.
14 *
15 * * Neither the name of the University of Southampton nor the names of its
16 * contributors may be used to endorse or promote products derived from this
17 * software without specific prior written permission.
18 *
19 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
20 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
21 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
22 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
23 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
24 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
25 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
26 * ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
27 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
28 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
29 */
30 package org.openimaj.ml.classification.cascade;
31
32 import org.openimaj.image.objectdetection.haar.StageTreeClassifier;
33
34 public class CascadeLearner {
35 float maximumFPRPerStage;
36 float minimumDRPerStage;
37 float targetFPR;
38
39 StageTreeClassifier learn() {
40 final float overallFPR = 1.0f;
41 final float overallDR = 1.0f;
42
43 float previousFPR = overallFPR;
44 final float previousDR = overallDR;
45 for (int i = 0; overallFPR > targetFPR; i++) {
46
47 for (int n = 0; overallFPR > maximumFPRPerStage * previousFPR; n++) {
48 // perform adaboost step
49
50 // evaluate on validation set (compute overallFPR and overallDR)
51
52 // decrease current stage threshold to achieve overallDR >=
53 // minimumDRPerStage*previousDR
54 // (recompute overallFPR at the same time)
55 }
56
57 previousFPR = overallFPR;
58 }
59
60 return null;
61 }
62 }