diff --git a/inference-engine/samples/common/samples/classification_results.h b/inference-engine/samples/common/samples/classification_results.h
index 12b4c10fcaf..f623d2c0f24 100644
--- a/inference-engine/samples/common/samples/classification_results.h
+++ b/inference-engine/samples/common/samples/classification_results.h
@@ -29,6 +29,7 @@ private:
     const std::vector<std::string> _labels;
     const std::vector<strType> _imageNames;
     const size_t _batchSize;
+    std::vector<unsigned> _results;
 
     void printHeader() {
         std::cout << _classidStr << " " << _probabilityStr;
@@ -123,20 +124,18 @@ public:
             _outBlob(std::move(output_blob)),
             _labels(std::move(labels)),
             _imageNames(std::move(image_names)),
-            _batchSize(batch_size) {
+            _batchSize(batch_size),
+            _results() {
         if (_imageNames.size() != _batchSize) {
             throw std::logic_error("Batch size should be equal to the number of images.");
         }
+        topResults(_nTop, *_outBlob, _results);
     }
 
     /**
     * @brief prints formatted classification results
     */
     void print() {
-        /** This vector stores id's of top N results **/
-        std::vector<unsigned> results;
-        topResults(_nTop, *_outBlob, results);
-
         /** Print the result iterating over each batch **/
         std::cout << std::endl << "Top " << _nTop << " results:" << std::endl << std::endl;
         for (unsigned int image_id = 0; image_id < _batchSize; ++image_id) {
@@ -160,19 +159,26 @@ public:
 
                 const auto result = moutputHolder.
                         as<const InferenceEngine::PrecisionTrait<InferenceEngine::Precision::FP32>::value_type*>()
-                [results[id] + image_id * (_outBlob->size() / _batchSize)];
+                [_results[id] + image_id * (_outBlob->size() / _batchSize)];
 
-                std::cout << std::setw(static_cast<int>(_classidStr.length())) << std::left << results[id] << " ";
+                std::cout << std::setw(static_cast<int>(_classidStr.length())) << std::left << _results[id] << " ";
                 std::cout << std::left << std::setw(static_cast<int>(_probabilityStr.length())) << std::fixed << result;
 
                 if (!_labels.empty()) {
-                    std::cout << " " + _labels[results[id]];
+                    std::cout << " " + _labels[_results[id]];
                 }
                 std::cout << std::endl;
             }
             std::cout << std::endl;
         }
     }
+
+    /**
+    * @brief returns the classification results in a vector
+    */
+    std::vector<unsigned> getResults() {
+        return _results;
+    }
 };
 
 using ClassificationResult = ClassificationResultT<>;