added openfabmap code, contributed by Arren Glover. fixed several warnings in the new versions of retina filters

modules/contrib/src/bowmsctrainer.cpp

@@ -0,0 +1,139 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+// This file originates from the openFABMAP project:
+// [http://code.google.com/p/openfabmap/]
+//
+// For published work which uses all or part of OpenFABMAP, please cite:
+// [http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6224843]
+//
+// Original Algorithm by Mark Cummins and Paul Newman:
+// [http://ijr.sagepub.com/content/27/6/647.short]
+// [http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5613942]
+// [http://ijr.sagepub.com/content/30/9/1100.abstract]
+//
+//                           License Agreement
+//
+// Copyright (C) 2012 Arren Glover [aj.glover@qut.edu.au] and
+//                    Will Maddern [w.maddern@qut.edu.au], all rights reserved.
+//
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "precomp.hpp"
+#include "opencv2/contrib/openfabmap.hpp"
+
+namespace cv {
+
+namespace of2 {
+
+BOWMSCTrainer::BOWMSCTrainer(double _clusterSize) :
+    clusterSize(_clusterSize) {
+}
+
+BOWMSCTrainer::~BOWMSCTrainer() {
+}
+
+Mat BOWMSCTrainer::cluster() const {
+    CV_Assert(!descriptors.empty());
+    int descCount = 0;
+    for(size_t i = 0; i < descriptors.size(); i++)
+    descCount += descriptors[i].rows;
+
+    Mat mergedDescriptors(descCount, descriptors[0].cols,
+        descriptors[0].type());
+    for(size_t i = 0, start = 0; i < descriptors.size(); i++)
+    {
+        Mat submut = mergedDescriptors.rowRange((int)start,
+            (int)(start + descriptors[i].rows));
+        descriptors[i].copyTo(submut);
+        start += descriptors[i].rows;
+    }
+    return cluster(mergedDescriptors);
+}
+
+Mat BOWMSCTrainer::cluster(const Mat& descriptors) const {
+
+    CV_Assert(!descriptors.empty());
+
+    // TODO: sort the descriptors before clustering.
+
+
+    Mat icovar = Mat::eye(descriptors.cols,descriptors.cols,descriptors.type());
+
+    vector<Mat> initialCentres;
+    initialCentres.push_back(descriptors.row(0));
+    for (int i = 1; i < descriptors.rows; i++) {
+        double minDist = DBL_MAX;
+        for (size_t j = 0; j < initialCentres.size(); j++) {
+            minDist = std::min(minDist,
+                cv::Mahalanobis(descriptors.row(i),initialCentres[j],
+                icovar));
+        }
+        if (minDist > clusterSize)
+            initialCentres.push_back(descriptors.row(i));
+    }
+
+    std::vector<std::list<cv::Mat> > clusters;
+    clusters.resize(initialCentres.size());
+    for (int i = 0; i < descriptors.rows; i++) {
+        int index = 0; double dist = 0, minDist = DBL_MAX;
+        for (size_t j = 0; j < initialCentres.size(); j++) {
+            dist = cv::Mahalanobis(descriptors.row(i),initialCentres[j],icovar);
+            if (dist < minDist) {
+                minDist = dist;
+                index = (int)j;
+            }
+        }
+        clusters[index].push_back(descriptors.row(i));
+    }
+
+    // TODO: throw away small clusters.
+
+    Mat vocabulary;
+    Mat centre = Mat::zeros(1,descriptors.cols,descriptors.type());
+    for (size_t i = 0; i < clusters.size(); i++) {
+        centre.setTo(0);
+        for (std::list<cv::Mat>::iterator Ci = clusters[i].begin(); Ci != clusters[i].end(); Ci++) {
+            centre += *Ci;
+        }
+        centre /= (double)clusters[i].size();
+        vocabulary.push_back(centre);
+    }
+
+    return vocabulary;
+}
+
+}
+
+}
+