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diff --git a/src/Subsampling/test/test_choose_n_farthest_points.cpp b/src/Subsampling/test/test_choose_n_farthest_points.cpp
new file mode 100644
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+++ b/src/Subsampling/test/test_choose_n_farthest_points.cpp
@@ -0,0 +1,102 @@
+/*    This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
+ *    See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
+ *    Author(s):       Siargey Kachanovich
+ *
+ *    Copyright (C) 2016 Inria
+ *
+ *    Modification(s):
+ *      - YYYY/MM Author: Description of the modification
+ */
+
+// #ifdef _DEBUG
+// # define TBB_USE_THREADING_TOOL
+// #endif
+
+#define BOOST_TEST_DYN_LINK
+#define BOOST_TEST_MODULE Subsampling - test choose_n_farthest_points
+#include <boost/test/unit_test.hpp>
+#include <boost/mpl/list.hpp>
+
+#include <gudhi/choose_n_farthest_points.h>
+#include <vector>
+#include <iterator>
+
+#include <CGAL/Epick_d.h>
+
+typedef CGAL::Epick_d<CGAL::Dynamic_dimension_tag> K;
+typedef typename K::FT FT;
+typedef typename K::Point_d Point_d;
+
+typedef boost::mpl::list<CGAL::Epick_d<CGAL::Dynamic_dimension_tag>, CGAL::Epick_d<CGAL::Dimension_tag<4>>> list_of_tested_kernels;
+
+BOOST_AUTO_TEST_CASE_TEMPLATE(test_choose_farthest_point, Kernel, list_of_tested_kernels) {
+  typedef typename Kernel::FT FT;
+  typedef typename Kernel::Point_d Point_d;
+  std::vector< Point_d > points, landmarks;
+  // Add grid points (625 points)
+  for (FT i = 0; i < 5; i += 1.0)
+    for (FT j = 0; j < 5; j += 1.0)
+      for (FT k = 0; k < 5; k += 1.0)
+        for (FT l = 0; l < 5; l += 1.0) {
+          std::vector<FT> point({i, j, k, l});
+          points.push_back(Point_d(point.begin(), point.end()));
+        }
+
+  landmarks.clear();
+  Kernel k;
+  Gudhi::subsampling::choose_n_farthest_points(k, points, 100, Gudhi::subsampling::random_starting_point, std::back_inserter(landmarks));
+
+  BOOST_CHECK(landmarks.size() == 100);
+  for (auto landmark : landmarks)
+  {
+    // Check all landmarks are in points
+    BOOST_CHECK(std::find (points.begin(), points.end(), landmark) != points.end());
+  }
+}
+
+BOOST_AUTO_TEST_CASE_TEMPLATE(test_choose_farthest_point_limits, Kernel, list_of_tested_kernels) {
+  typedef typename Kernel::FT FT;
+  typedef typename Kernel::Point_d Point_d;
+  std::vector< Point_d > points, landmarks;
+  std::vector< FT > distances;
+  landmarks.clear();
+  Kernel k;
+  // Choose -1 farthest points in an empty point cloud
+  Gudhi::subsampling::choose_n_farthest_points(k, points, -1, -1, std::back_inserter(landmarks), std::back_inserter(distances));
+  BOOST_CHECK(landmarks.size() == 0);
+  landmarks.clear(); distances.clear();
+  // Choose 0 farthest points in an empty point cloud
+  Gudhi::subsampling::choose_n_farthest_points(k, points, 0, -1, std::back_inserter(landmarks), std::back_inserter(distances));
+  BOOST_CHECK(landmarks.size() == 0);
+  landmarks.clear(); distances.clear();
+  // Choose 1 farthest points in an empty point cloud
+  Gudhi::subsampling::choose_n_farthest_points(k, points, 1, -1, std::back_inserter(landmarks), std::back_inserter(distances));
+  BOOST_CHECK(landmarks.size() == 0);
+  landmarks.clear(); distances.clear();
+
+  std::vector<FT> point({0.0, 0.0, 0.0, 0.0});
+  points.push_back(Point_d(point.begin(), point.end()));
+  // Choose -1 farthest points in a one point cloud
+  Gudhi::subsampling::choose_n_farthest_points(k, points, -1, -1, std::back_inserter(landmarks), std::back_inserter(distances));
+  BOOST_CHECK(landmarks.size() == 1 && distances.size() == 1);
+  BOOST_CHECK(distances[0] == std::numeric_limits<FT>::infinity());
+  landmarks.clear(); distances.clear();
+  // Choose 0 farthest points in a one point cloud
+  Gudhi::subsampling::choose_n_farthest_points(k, points, 0, -1, std::back_inserter(landmarks), std::back_inserter(distances));
+  BOOST_CHECK(landmarks.size() == 0 && distances.size() == 0);
+  landmarks.clear(); distances.clear();
+  // Choose 1 farthest points in a one point cloud
+  Gudhi::subsampling::choose_n_farthest_points(k, points, 1, -1, std::back_inserter(landmarks), std::back_inserter(distances));
+  BOOST_CHECK(landmarks.size() == 1 && distances.size() == 1);
+  BOOST_CHECK(distances[0] == std::numeric_limits<FT>::infinity());
+  landmarks.clear(); distances.clear();
+
+  std::vector<FT> point2({1.0, 0.0, 0.0, 0.0});
+  points.push_back(Point_d(point2.begin(), point2.end()));
+  // Choose all farthest points in a one point cloud
+  Gudhi::subsampling::choose_n_farthest_points(k, points, -1, -1, std::back_inserter(landmarks), std::back_inserter(distances));
+  BOOST_CHECK(landmarks.size() == 2 && distances.size() == 2);
+  BOOST_CHECK(distances[0] == std::numeric_limits<FT>::infinity());
+  BOOST_CHECK(distances[1] == 1);
+  landmarks.clear(); distances.clear();
+}