diff --git a/src/cpp/flann/algorithms/dist.h b/src/cpp/flann/algorithms/dist.h
index 280d8244086ad8cf6ed6323b8f87fb43fd13d335..689b3136ed9db494bcba877c8d93a69d38753bc4 100644
--- a/src/cpp/flann/algorithms/dist.h
+++ b/src/cpp/flann/algorithms/dist.h
@@ -79,14 +79,6 @@ template<>
 struct Accumulator<int> { typedef float Type; };
 
 
-class TrueType
-{
-};
-
-class FalseType
-{
-};
-
 
 /**
  * Squared Euclidean distance functor.
diff --git a/src/cpp/flann/algorithms/lsh_index.h b/src/cpp/flann/algorithms/lsh_index.h
index b875181fdf4e07cb717ab22d31d3218b7277699e..cd0f21e4f3761ffe30bafbd604e4ae8ecee9a2bd 100644
--- a/src/cpp/flann/algorithms/lsh_index.h
+++ b/src/cpp/flann/algorithms/lsh_index.h
@@ -198,7 +198,7 @@ public:
         assert(dists.cols >= knn);
 
         int count = 0;
-        if (params.use_heap==True) {
+        if (params.use_heap==FLANN_True) {
         	KNNUniqueResultSet<DistanceType> resultSet(knn);
         	for (size_t i = 0; i < queries.rows; i++) {
         		resultSet.clear();
@@ -239,7 +239,7 @@ public:
 		if (dists.size() < queries.rows ) dists.resize(queries.rows);
 
 		int count = 0;
-		if (params.use_heap==True) {
+		if (params.use_heap==FLANN_True) {
 			KNNUniqueResultSet<DistanceType> resultSet(knn);
 			for (size_t i = 0; i < queries.rows; i++) {
 				resultSet.clear();
diff --git a/src/cpp/flann/algorithms/nn_index.h b/src/cpp/flann/algorithms/nn_index.h
index bf0333e7717656d86cd65f2c0d1c5012f60a036c..e2f26c7bcde710809b50f222a41320436e33a807 100644
--- a/src/cpp/flann/algorithms/nn_index.h
+++ b/src/cpp/flann/algorithms/nn_index.h
@@ -89,11 +89,11 @@ public:
         assert(dists.cols >= knn);
         bool use_heap;
 
-        if (params.use_heap==Undefined) {
+        if (params.use_heap==FLANN_Undefined) {
         	use_heap = (knn>KNN_HEAP_THRESHOLD)?true:false;
         }
         else {
-        	use_heap = (params.use_heap==True)?true:false;
+        	use_heap = (params.use_heap==FLANN_True)?true:false;
         }
         int count = 0;
 
@@ -161,11 +161,11 @@ public:
     {
         assert(queries.cols == veclen());
         bool use_heap;
-        if (params.use_heap==Undefined) {
+        if (params.use_heap==FLANN_Undefined) {
         	use_heap = (knn>KNN_HEAP_THRESHOLD)?true:false;
         }
         else {
-        	use_heap = (params.use_heap==True)?true:false;
+        	use_heap = (params.use_heap==FLANN_True)?true:false;
         }
 
         if (indices.size() < queries.rows ) indices.resize(queries.rows);
diff --git a/src/cpp/flann/tbb/bodies.hpp b/src/cpp/flann/tbb/bodies.hpp
index 992aae91fbc854b72a9b31461a6e192fe9681267..2bcab762cea60f7e6159444c60ad9db2498901f3 100644
--- a/src/cpp/flann/tbb/bodies.hpp
+++ b/src/cpp/flann/tbb/bodies.hpp
@@ -79,7 +79,7 @@ public:
    */
   void operator()( const tbb::blocked_range<size_t>& r ) const
   {
-    if (params_.use_heap==True)
+    if (params_.use_heap==FLANN_True)
     {
       KNNResultSet2<DistanceType> resultSet(knn_);
       for (size_t i=r.begin(); i!=r.end(); ++i)
@@ -169,7 +169,7 @@ public:
    */
   void operator()( const tbb::blocked_range<size_t>& r ) const
   {
-    if (params_.use_heap==True) {
+    if (params_.use_heap==FLANN_True) {
         KNNResultSet2<DistanceType> resultSet(knn_);
         for (size_t i=r.begin(); i!=r.end(); ++i)
         {
diff --git a/src/cpp/flann/util/params.h b/src/cpp/flann/util/params.h
index 99d3e92e182705fe799aea7ba47c7482fa9faab4..72b73b0bc0e2620cceaf292579701af1e9cd9314 100644
--- a/src/cpp/flann/util/params.h
+++ b/src/cpp/flann/util/params.h
@@ -43,9 +43,9 @@ typedef std::map<std::string, any> IndexParams;
 
 
 typedef enum {
-	False = 0,
-	True = 1,
-	Undefined
+	FLANN_False = 0,
+	FLANN_True = 1,
+	FLANN_Undefined
 } tri_type;
 
 struct SearchParams
@@ -54,7 +54,7 @@ struct SearchParams
     	checks(checks_), eps(eps_), sorted(sorted_)
     {
     	max_neighbors = -1;
-    	use_heap = Undefined;
+    	use_heap = FLANN_Undefined;
     	cores = 1;
     	matrices_in_gpu_ram = false;
     }
@@ -67,7 +67,7 @@ struct SearchParams
     bool sorted;
     // maximum number of neighbors radius search should return (-1 for unlimited)
     int max_neighbors;
-    // use a heap to manage the result set (default: Undefined)
+    // use a heap to manage the result set (default: FLANN_Undefined)
     tri_type use_heap;
     // how many cores to assign to the search
     // this parameter will be ignored if Intel TBB isn't available on the system or no "TBB" macro is defined