diff --git a/modules/gpu/perf/perf_objdetect.cpp b/modules/gpu/perf/perf_objdetect.cpp
index a86337112..2224194bb 100644
--- a/modules/gpu/perf/perf_objdetect.cpp
+++ b/modules/gpu/perf/perf_objdetect.cpp
@@ -89,11 +89,90 @@ PERF_TEST_P(HOG, CalTech, Values<string>("gpu/caltech/image_00000009_0.png", "gp
     SANITY_CHECK(found_locations);
 }
 
+//================================================= ICF SoftCascade =================================================//
+
 typedef pair<string, string> pair_string;
 DEF_PARAM_TEST_1(SoftCascade, pair_string);
 
-PERF_TEST_P(SoftCascade, detect, Values<pair_string>(make_pair("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml",
-                                                              "cv/cascadeandhog/bahnhof/image_00000000_0.png")))
+
+// struct SoftCascadeTest : public perf::TestBaseWithParam<roi_fixture_t>
+// {
+//     typedef cv::gpu::SoftCascade::Detection detection_t;
+//     static cv::Rect getFromTable(int idx)
+//     {
+//         static const cv::Rect rois[] =
+//         {
+//             cv::Rect( 65,  20,  35, 80),
+//             cv::Rect( 95,  35,  45, 40),
+//             cv::Rect( 45,  35,  45, 40),
+//             cv::Rect( 25,  27,  50, 45),
+//             cv::Rect(100,  50,  45, 40),
+
+//             cv::Rect( 60,  30,  45, 40),
+//             cv::Rect( 40,  55,  50, 40),
+//             cv::Rect( 48,  37,  72, 80),
+//             cv::Rect( 48,  32,  85, 58),
+//             cv::Rect( 48,   0,  32, 27)
+//         };
+
+//         return rois[idx];
+//     }
+
+//     static std::string itoa(long i)
+//     {
+//         static char s[65];
+//         sprintf(s, "%ld", i);
+//         return std::string(s);
+//     }
+
+//     static std::string getImageName(int level)
+//     {
+//         time_t rawtime;
+//         struct tm * timeinfo;
+//         char buffer [80];
+
+//         time ( &rawtime );
+//         timeinfo = localtime ( &rawtime );
+
+//         strftime (buffer,80,"%Y-%m-%d--%H-%M-%S",timeinfo);
+//         return "gpu_rec_level_" + itoa(level)+ "_" + std::string(buffer) + ".png";
+//     }
+
+//     static void print(std::ostream &out, const detection_t& d)
+//     {
+//         out << "\x1b[32m[ detection]\x1b[0m ("
+//             << std::setw(4)  << d.x
+//             << " "
+//             << std::setw(4)  << d.y
+//             << ") ("
+//             << std::setw(4)  << d.w
+//             << " "
+//             << std::setw(4)  << d.h
+//             << ") "
+//             << std::setw(12) << d.confidence
+//             <<  std::endl;
+//     }
+
+//     static void printTotal(std::ostream &out, int detbytes)
+//     {
+//         out << "\x1b[32m[          ]\x1b[0m Total detections " << (detbytes / sizeof(detection_t)) << std::endl;
+//     }
+
+//     static void writeResult(const cv::Mat& result, const int level)
+//     {
+//         std::string path = cv::tempfile(getImageName(level).c_str());
+//         cv::imwrite(path, result);
+//         std::cout << "\x1b[32m" << "[          ]" << std::endl << "[ stored in]"<< "\x1b[0m" << path << std::endl;
+//     }
+// };
+
+typedef std::tr1::tuple<std::string, std::string> fixture_t;
+typedef perf::TestBaseWithParam<fixture_t> SoftCascadeTest;
+
+PERF_TEST_P(SoftCascadeTest, detect,
+    testing::Combine(
+        testing::Values(std::string("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")),
+        testing::Values(std::string("cv/cascadeandhog/bahnhof/image_00000000_0.png"))))
 {
     if (runOnGpu)
     {
@@ -133,6 +212,110 @@ PERF_TEST_P(SoftCascade, detect, Values<pair_string>(make_pair("cv/cascadeandhog
     }
 }
 
+static cv::Rect getFromTable(int idx)
+{
+    static const cv::Rect rois[] =
+    {
+        cv::Rect( 65,  20,  35, 80),
+        cv::Rect( 95,  35,  45, 40),
+        cv::Rect( 45,  35,  45, 40),
+        cv::Rect( 25,  27,  50, 45),
+        cv::Rect(100,  50,  45, 40),
+
+        cv::Rect( 60,  30,  45, 40),
+        cv::Rect( 40,  55,  50, 40),
+        cv::Rect( 48,  37,  72, 80),
+        cv::Rect( 48,  32,  85, 58),
+        cv::Rect( 48,   0,  32, 27)
+    };
+
+    return rois[idx];
+}
+
+typedef std::tr1::tuple<std::string, std::string, int> roi_fixture_t;
+typedef perf::TestBaseWithParam<roi_fixture_t> SoftCascadeTestRoi;
+
+PERF_TEST_P(SoftCascadeTestRoi, detectInRoi,
+    testing::Combine(
+        testing::Values(std::string("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")),
+        testing::Values(std::string("cv/cascadeandhog/bahnhof/image_00000000_0.png")),
+        testing::Range(0, 5)))
+{
+    if (runOnGpu)
+    {
+        cv::Mat cpu = readImage (GET_PARAM(1));
+        ASSERT_FALSE(cpu.empty());
+        cv::gpu::GpuMat colored(cpu);
+
+        cv::gpu::SoftCascade cascade;
+        ASSERT_TRUE(cascade.load(perf::TestBase::getDataPath(GET_PARAM(0))));
+
+        cv::gpu::GpuMat objectBoxes(1, 16384 * 20, CV_8UC1), rois(cascade.getRoiSize(), CV_8UC1);
+        rois.setTo(0);
+
+        int nroi = GET_PARAM(2);
+        cv::RNG rng;
+        for (int i = 0; i < nroi; ++i)
+        {
+            cv::Rect r = getFromTable(rng(10));
+            cv::gpu::GpuMat sub(rois, r);
+            sub.setTo(1);
+        }
+
+        cv::gpu::GpuMat curr = objectBoxes;
+        cascade.detectMultiScale(colored, rois, curr);
+
+        TEST_CYCLE()
+        {
+            curr = objectBoxes;
+            cascade.detectMultiScale(colored, rois, curr);
+        }
+    }
+    else
+    {
+        FAIL();
+    }
+}
+
+PERF_TEST_P(SoftCascadeTestRoi, detectEachRoi,
+    testing::Combine(
+        testing::Values(std::string("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")),
+        testing::Values(std::string("cv/cascadeandhog/bahnhof/image_00000000_0.png")),
+        testing::Range(0, 10)))
+{
+    if (runOnGpu)
+    {
+        cv::Mat cpu = readImage (GET_PARAM(1));
+        ASSERT_FALSE(cpu.empty());
+        cv::gpu::GpuMat colored(cpu);
+
+        cv::gpu::SoftCascade cascade;
+        ASSERT_TRUE(cascade.load(perf::TestBase::getDataPath(GET_PARAM(0))));
+
+        cv::gpu::GpuMat objectBoxes(1, 16384 * 20, CV_8UC1), rois(cascade.getRoiSize(), CV_8UC1);
+        rois.setTo(0);
+
+        int idx = GET_PARAM(2);
+        cv::Rect r = getFromTable(idx);
+        cv::gpu::GpuMat sub(rois, r);
+        sub.setTo(1);
+
+        cv::gpu::GpuMat curr = objectBoxes;
+        cascade.detectMultiScale(colored, rois, curr);
+
+        TEST_CYCLE()
+        {
+            curr = objectBoxes;
+            cascade.detectMultiScale(colored, rois, curr);
+        }
+    }
+    else
+    {
+        FAIL();
+    }
+}
+
+
 ///////////////////////////////////////////////////////////////
 // HaarClassifier