diff --git a/openbr/plugins/cluster/onlinerod.cpp b/openbr/plugins/cluster/onlinerod.cpp
deleted file mode 100644
index acf5634..0000000
--- a/openbr/plugins/cluster/onlinerod.cpp
+++ /dev/null
@@ -1,125 +0,0 @@
-#include <openbr/plugins/openbr_internal.h>
-#include <openbr/core/cluster.h>
-#include <openbr/core/opencvutils.h>
-
-using namespace cv;
-
-namespace br
-{
-
-/*!
- * \brief Constructors clusters based on the Rank-Order distance in an online, incremental manner
- * \author Charles Otto \cite caotto
- * \author Jordan Cheney \cite JordanCheney
- * \br_property br::Distance* distance Distance to compute the similarity score between templates. Default is L2.
- * \br_property int kNN Maximum number of nearest neighbors to keep for each template. Default is 20.
- * \br_property float aggression Clustering aggresiveness. A higher value will result in larger clusters. Default is 10.
- * \br_property bool incremental If true, compute the clusters as each template is processed otherwise compute the templates at the end. Default is false.
- * \br_property QString evalOutput Path to store cluster informtation. Optional. Default is an empty string.
- * \br_paper Zhu et al.
- *           "A Rank-Order Distance based Clustering Algorithm for Face Tagging"
- *           CVPR 2011
- */
-class OnlineRODTransform : public TimeVaryingTransform
-{
-    Q_OBJECT
-    Q_PROPERTY(br::Distance *distance READ get_distance WRITE set_distance RESET reset_distance STORED true)
-    Q_PROPERTY(int kNN READ get_kNN WRITE set_kNN RESET reset_kNN STORED false)
-    Q_PROPERTY(float aggression READ get_aggression WRITE set_aggression RESET reset_aggression STORED false)
-    Q_PROPERTY(bool incremental READ get_incremental WRITE set_incremental RESET reset_incremental STORED false)
-    Q_PROPERTY(QString evalOutput READ get_evalOutput WRITE set_evalOutput RESET reset_evalOutput STORED false)
-
-    BR_PROPERTY(br::Distance*, distance, Distance::make(".Dist(L2)",this))
-    BR_PROPERTY(int, kNN, 20)
-    BR_PROPERTY(float, aggression, 10)
-    BR_PROPERTY(bool, incremental, false)
-    BR_PROPERTY(QString, evalOutput, "")
-
-    TemplateList templates;
-    Neighborhood neighborhood;
-
-public:
-    OnlineRODTransform() : TimeVaryingTransform(false, false) {}
-
-private:
-    void projectUpdate(const TemplateList &src, TemplateList &dst)
-    {
-        // update current graph
-        foreach(const Template &t, src) {
-            QList<float> scores = distance->compare(templates, t);
-
-            // attempt to udpate each existing point's (sorted) k-NN list with these results.
-            Neighbors currentN;
-            for (int i=0; i < scores.size(); i++) {
-                currentN.append(Neighbor(i, scores[i]));
-                Neighbors target = neighborhood[i];
-
-                // should we insert the new neighbor into the current target's list?
-                if (target.size() < kNN || scores[i] > target.last().second) {
-                    // insert into the sorted nearest neighbor list
-                    Neighbor temp(scores.size(), scores[i]);
-                    br::Neighbors::iterator res = qLowerBound(target.begin(), target.end(), temp, compareNeighbors);
-                    target.insert(res, temp);
-
-                    if (target.size() > kNN)
-                        target.removeLast();
-
-                    neighborhood[i] = target;
-                }
-            }
-
-            // add a new row, consisting of the top neighbors of the newest point
-            int actuallyKeep = std::min(kNN, currentN.size());
-            std::partial_sort(currentN.begin(), currentN.begin()+actuallyKeep, currentN.end(), compareNeighbors);
-
-            Neighbors selected = currentN.mid(0, actuallyKeep);
-            neighborhood.append(selected);
-            templates.append(t);
-        }
-
-        if (incremental)
-            identifyClusters(dst);
-    }
-
-    void finalize(TemplateList &output)
-    {
-        if (!templates.empty()) {
-            identifyClusters(output);
-            templates.clear();
-            neighborhood.clear();
-        }
-    }
-
-    void identifyClusters(TemplateList &dst)
-    {
-        Clusters clusters = ClusterGraph(neighborhood, aggression, evalOutput);
-        if (Globals->verbose)
-            qDebug("Built %d clusters from %d templates", clusters.size(), templates.size());
-
-        for (int i = 0; i < clusters.size(); i++) {
-            // Calculate the centroid of each cluster
-            Mat center = Mat::zeros(templates[0].m().rows, templates[0].m().cols, CV_32F);
-            foreach (int t, clusters[i]) {
-                Mat converted; templates[t].m().convertTo(converted, CV_32F);
-                center += converted;
-            }
-            center /= clusters[i].size();
-
-            // Calculate the Euclidean distance from the center to use as the cluster confidence
-            foreach (int t, clusters[i]) {
-                templates[t].file.set("Cluster", i);
-                Mat c; templates[t].m().convertTo(c, CV_32F);
-                Mat p; pow(c - center, 2, p);
-                templates[t].file.set("ClusterConfidence", sqrt(sum(p)[0]));
-            }
-        }
-        dst.append(templates);
-    }
-};
-
-BR_REGISTER(Transform, OnlineRODTransform)
-
-} // namespace br
-
-#include "onlinerod.moc"
-