diff --git a/modules/gpu/src/brute_force_matcher.cpp b/modules/gpu/src/brute_force_matcher.cpp
index f4f53fc0dabcc7d78fd1529c4efb1fe450d670ad..86b74e4fe79ab601a7c852a83b28eecb6b010af2 100644
--- a/modules/gpu/src/brute_force_matcher.cpp
+++ b/modules/gpu/src/brute_force_matcher.cpp
@@ -446,10 +446,17 @@ void cv::gpu::BruteForceMatcher_GPU_base::knnMatch(const GpuMat& queryDescs, con
     const int nQuery = queryDescs.rows;
     const int nTrain = trainDescs.rows;
 
-    ensureSizeIsEnough(nQuery, k, CV_32S, trainIdx);
-    ensureSizeIsEnough(nQuery, k, CV_32F, distance);
-    if (k != 2)
+    if (k == 2)
+    {
+        ensureSizeIsEnough(1, nQuery, CV_32SC2, trainIdx);
+        ensureSizeIsEnough(1, nQuery, CV_32FC2, distance);
+    }
+    else
+    {
+        ensureSizeIsEnough(nQuery, k, CV_32S, trainIdx);
+        ensureSizeIsEnough(nQuery, k, CV_32F, distance);
         ensureSizeIsEnough(nQuery, nTrain, CV_32FC1, allDist);
+    }
 
     if (stream)
     {
@@ -491,14 +498,19 @@ void cv::gpu::BruteForceMatcher_GPU_base::knnMatchConvert(const Mat& trainIdx, c
     if (trainIdx.empty() || distance.empty())
         return;
 
-    CV_Assert(trainIdx.type() == CV_32SC1);
-    CV_Assert(distance.type() == CV_32FC1 && distance.size() == trainIdx.size());
+    CV_Assert(trainIdx.type() == CV_32SC2 || trainIdx.type() == CV_32SC1);
+    CV_Assert(distance.type() == CV_32FC2 || distance.type() == CV_32FC1);
+    CV_Assert(distance.size() == trainIdx.size());
+    CV_Assert(trainIdx.isContinuous() && distance.isContinuous());
 
-    const int nQuery = distance.rows;
-    const int k = trainIdx.cols;
+    const int nQuery = trainIdx.type() == CV_32SC2 ? trainIdx.cols : trainIdx.rows;
+    const int k = trainIdx.type() == CV_32SC2 ? 2 :trainIdx.cols;
 
     matches.clear();
     matches.reserve(nQuery);
+    
+    const int* trainIdx_ptr = trainIdx.ptr<int>();
+    const float* distance_ptr = distance.ptr<float>();
 
     for (int queryIdx = 0; queryIdx < nQuery; ++queryIdx)
     {
@@ -506,8 +518,6 @@ void cv::gpu::BruteForceMatcher_GPU_base::knnMatchConvert(const Mat& trainIdx, c
         vector<DMatch>& curMatches = matches.back();
         curMatches.reserve(k);
 
-        const int* trainIdx_ptr = trainIdx.ptr<int>(queryIdx);
-        const float* distance_ptr = distance.ptr<float>(queryIdx);
         for (int i = 0; i < k; ++i, ++trainIdx_ptr, ++distance_ptr)
         {
             int trainIdx = *trainIdx_ptr;
diff --git a/modules/gpu/src/cuda/brute_force_matcher.cu b/modules/gpu/src/cuda/brute_force_matcher.cu
index c2c7317b1a1b3164f311711185ead382a93530a1..efe3510149de771cddf3f1d328549c302bd96d7e 100644
--- a/modules/gpu/src/cuda/brute_force_matcher.cu
+++ b/modules/gpu/src/cuda/brute_force_matcher.cu
@@ -452,7 +452,7 @@ namespace cv { namespace gpu { namespace bfmatcher
     }
 
     template <int BLOCK_DIM_X, int BLOCK_DIM_Y, typename VecDiff, typename Dist, typename T, typename Mask>
-    __global__ void knnMatch2(const PtrStep_<T> query, const DevMem2D_<T> train, const Mask m, PtrStep_<int2> trainIdx, PtrStep_<float2> distance)
+    __global__ void knnMatch2(const PtrStep_<T> query, const DevMem2D_<T> train, const Mask m, int2* trainIdx, float2* distance)
     {
         typedef typename Dist::result_type result_type;
         typedef typename Dist::value_type value_type;
@@ -520,8 +520,8 @@ namespace cv { namespace gpu { namespace bfmatcher
                 }
             }
 
-            trainIdx.ptr(queryIdx)[0] = make_int2(bestTrainIdx1, bestTrainIdx2);
-            distance.ptr(queryIdx)[0] = make_float2(distMin1, distMin2);
+            trainIdx[queryIdx] = make_int2(bestTrainIdx1, bestTrainIdx2);
+            distance[queryIdx] = make_float2(distMin1, distMin2);
         }
     }
 
@@ -556,7 +556,7 @@ namespace cv { namespace gpu { namespace bfmatcher
         const dim3 threads(BLOCK_DIM_X, BLOCK_DIM_Y, 1);
 
         knnMatch2<BLOCK_DIM_X, BLOCK_DIM_Y, VecDiffCachedRegister<BLOCK_DIM_X, MAX_LEN, LEN_EQ_MAX_LEN, typename Dist::value_type>, Dist, T>
-              <<<grid, threads, 0, stream>>>(query, train, mask, trainIdx, distance);
+              <<<grid, threads, 0, stream>>>(query, train, mask, trainIdx.data, distance.data);
         cudaSafeCall( cudaGetLastError() );
 
         if (stream == 0)