diff --git a/openbr/plugins/cluster/meanshift.cpp b/openbr/plugins/cluster/meanshift.cpp
deleted file mode 100644
index 6bd0324..0000000
--- a/openbr/plugins/cluster/meanshift.cpp
+++ /dev/null
@@ -1,124 +0,0 @@
-#include <openbr/plugins/openbr_internal.h>
-#include <openbr/core/opencvutils.h>
-
-using namespace cv;
-
-namespace br
-{
-
-/*!
- * \brief A transform implementing the mean shift clustering algorithm.
- * \author Jordan Cheney \cite JordanCheney
- * \br_property br::Distance* distance The distance used to compute the distance between templates
- * \br_property int kernelBandwidth The size of the kernel used to converge points to a cluster center
- * \br_property float shiftThreshold The cutoff threshold distance for a shifted point. A value lower then this threshold indicates a point has finished shifting to a cluster center.
- * \br_property float distanceThreshold The distance threshold for a point to join a cluster. A point must be at least this close to another point to be included in the same cluster as that point.
- * \br_link http://spin.atomicobject.com/2015/05/26/mean-shift-clustering/
- */
-class MeanShiftClusteringTransform : public TimeVaryingTransform
-{
-    Q_OBJECT
-
-    Q_PROPERTY(br::Distance* distance READ get_distance WRITE set_distance RESET reset_distance STORED false)
-    Q_PROPERTY(int kernelBandwidth READ get_kernelBandwidth WRITE set_kernelBandwidth RESET reset_kernelBandwidth STORED false)
-    Q_PROPERTY(float shiftThreshold READ get_shiftThreshold WRITE set_shiftThreshold RESET reset_shiftThreshold STORED false)
-    Q_PROPERTY(float distanceThreshold READ get_distanceThreshold WRITE set_distanceThreshold RESET reset_distanceThreshold STORED false)
-    BR_PROPERTY(br::Distance*, distance, Distance::make(".Dist(L2, false)", NULL))
-    BR_PROPERTY(int, kernelBandwidth, 3)
-    BR_PROPERTY(float, shiftThreshold, 1e-3)
-    BR_PROPERTY(float, distanceThreshold, 1e-1)
-
-public:
-    MeanShiftClusteringTransform() : TimeVaryingTransform(false, false) {}
-
-private:
-    void projectUpdate(const TemplateList &src, TemplateList &)
-    {
-        templates.append(src);
-    }
-
-    void finalize(TemplateList &output)
-    {
-        output.clear();
-
-        QList<Mat> original_points, shifted_points;
-        original_points = shifted_points = templates.data();
-
-        Mat shift_mask = Mat::zeros(1, shifted_points.size(), CV_32S);
-        while (countNonZero(shift_mask) != shifted_points.size()) {
-            for (int i = 0; i < shifted_points.size(); i++) {
-                if (shift_mask.at<int>(0, i))
-                    continue;
-
-                Mat point = shifted_points[i];
-                Mat shifted_point = point.clone();
-                meanshift(shifted_point, original_points);
-
-                float dist = distance->compare(point, shifted_point);
-                if (dist < shiftThreshold)
-                    shift_mask.at<int>(0, i) = 1;
-
-                shifted_points[i] = shifted_point;
-            }
-        }
-
-        QList<int> clusters = assignClusterID(shifted_points);
-        for (int i = 0; i < templates.size(); i++)
-            templates[i].file.set("Cluster", clusters[i]);
-        output.append(templates);
-    }
-
-    void meanshift(Mat &point, const QList<Mat> &original_points)
-    {
-        Mat distances(1, original_points.size(), CV_32FC1);
-        for (int i = 0; i < original_points.size(); i++)
-            distances.at<float>(0, i) = distance->compare(point, original_points[i]);
-
-        Mat weights = gaussianKernel(distances, kernelBandwidth);
-        point = (weights * OpenCVUtils::toMat(original_points)) /  sum(weights)[0];
-    }
-
-    inline Mat gaussianKernel(const Mat &distance, const float bandwidth)
-    {
-        Mat p, e;
-        pow(distance / bandwidth, 2, p);
-        exp(-0.5 * p, e);
-
-        return (1.0 / (bandwidth * sqrt(2 * CV_PI))) * e;
-    }
-
-    QList<int> assignClusterID(const QList<Mat> &points)
-    {
-        QList<int> groups;
-        int newGroupIdx = 0;
-        foreach (const Mat &point, points) {
-            int group = nearestGroup(point, points, groups);
-            if (group < 0)
-                group = newGroupIdx++;
-            groups.append(group);
-        }
-
-        if (Globals->verbose)
-            qDebug("created %d clusters from %d templates", newGroupIdx, points.size());
-
-        return groups;
-    }
-
-    int nearestGroup(const Mat &point, const QList<Mat> &points, const QList<int> groups)
-    {
-        for (int i = 0; i < groups.size(); i++) {
-            float dist = distance->compare(point, points[i]);
-            if (dist < distanceThreshold)
-                return groups[i];
-        }
-        return -1;
-    }
-
-    TemplateList templates;
-};
-
-BR_REGISTER(Transform, MeanShiftClusteringTransform)
-
-} // namespace br
-
-#include "cluster/meanshift.moc"