diff --git a/example/MouseExample.h b/example/MouseExample.h
index 0be86509..14fe49f5 100644
--- a/example/MouseExample.h
+++ b/example/MouseExample.h
@@ -37,8 +37,8 @@ void MouseTracking(cv::CommandLineParser parser)
 
 	cv::Mat frame = cv::Mat(800, 800, CV_8UC3);
 
-	if (!writer.isOpened())
-		writer.open(outFile, cv::VideoWriter::fourcc('P', 'I', 'M', '1'), 20, frame.size(), true);
+	if (!outFile.empty() && !writer.isOpened())
+		writer.open(outFile, cv::VideoWriter::fourcc('h', '2', '6', '4'), 20, frame.size(), true);
 
 	// Set mouse callback
 	cv::Point2f pointXY;
diff --git a/example/main.cpp b/example/main.cpp
index 4c385c1d..1fdf343a 100644
--- a/example/main.cpp
+++ b/example/main.cpp
@@ -43,100 +43,6 @@ const char* keys =
 
 // ----------------------------------------------------------------------
 
-#pragma once
-
-///
-/// \brief The EmbeddingsCalculator class
-///
-class EmbeddingsCalculatorSimple
-{
-public:
-	EmbeddingsCalculatorSimple() = default;
-	virtual ~EmbeddingsCalculatorSimple() = default;
-
-	///
-	bool Initialize(const std::string& cfgName, const std::string& weightsName, const cv::Size& inputLayer)
-	{
-		m_inputLayer = inputLayer;
-
-#if 1
-		m_net = cv::dnn::readNet(weightsName);
-#else
-		m_net = cv::dnn::readNetFromTorch(weightsName);
-#endif
-		if (!m_net.empty())
-		{
-			//m_net.setPreferableBackend(cv::dnn::DNN_BACKEND_INFERENCE_ENGINE);
-			//m_net.setPreferableTarget(cv::dnn::DNN_TARGET_CPU);
-
-			auto outNames = m_net.getUnconnectedOutLayersNames();
-			auto outLayers = m_net.getUnconnectedOutLayers();
-			auto outLayerType = m_net.getLayer(outLayers[0])->type;
-
-			std::vector<cv::dnn::MatShape> outputs;
-			std::vector<cv::dnn::MatShape> internals;
-			m_net.getLayerShapes(cv::dnn::MatShape(), 0, outputs, internals);
-			std::cout << "REID: getLayerShapes: outputs (" << outputs.size() << ") = " << (outputs.size() > 0 ? outputs[0].size() : 0) << ", internals (" << internals.size() << ") = " << (internals.size() > 0 ? internals[0].size() : 0) << std::endl;
-			if (outputs.size() && outputs[0].size() > 3)
-				std::cout << "outputs = [" << outputs[0][0] << ", " << outputs[0][1] << ", " << outputs[0][2] << ", " << outputs[0][3] << "], internals = [" << internals[0][0] << ", " << internals[0][1] << ", " << internals[0][2] << ", " << internals[0][3] << "]" << std::endl;
-		}
-		return !m_net.empty();
-	}
-
-	///
-	bool IsInitialized() const
-	{
-		return !m_net.empty();
-	}
-
-	///
-	cv::Mat Calc(const cv::Mat& img, cv::Rect rect)
-	{
-		auto Clamp = [](int& v, int& size, int hi) -> int
-		{
-			int res = 0;
-			if (v < 0)
-			{
-				res = v;
-				v = 0;
-				return res;
-			}
-			else if (v + size > hi - 1)
-			{
-				res = v;
-				v = hi - 1 - size;
-				if (v < 0)
-				{
-					size += v;
-					v = 0;
-				}
-				res -= v;
-				return res;
-			}
-			return res;
-		};
-		Clamp(rect.x, rect.width, img.cols);
-		Clamp(rect.y, rect.height, img.rows);
-
-		cv::Mat obj;
-		cv::resize(img(rect), obj, m_inputLayer, 0., 0., cv::INTER_CUBIC);
-		cv::Mat blob = cv::dnn::blobFromImage(obj, 1.0 / 255.0, cv::Size(), cv::Scalar(), false, false, CV_32F);
-
-		m_net.setInput(blob);
-		cv::Mat embedding;
-		std::cout << "embedding: " << embedding.size() << ", chans = " << embedding.channels() << std::endl;
-		//std::cout << "orig: " << embedding << std::endl;
-		cv::normalize(m_net.forward(), embedding);
-		//std::cout << "normalized: " << embedding << std::endl;
-		return embedding;
-	}
-
-private:
-	cv::dnn::Net m_net;
-	cv::Size m_inputLayer{ 128, 256 };
-};
-
-
 int main(int argc, char** argv)
 {
     cv::CommandLineParser parser(argc, argv, keys);
@@ -148,39 +54,6 @@ int main(int argc, char** argv)
     cv::ocl::setUseOpenCL(useOCL);
     std::cout << (cv::ocl::useOpenCL() ? "OpenCL is enabled" : "OpenCL not used") << std::endl;
 
-#if 0
-	EmbeddingsCalculatorSimple ec;
-	ec.Initialize("C:/work/home/mtracker/tmp/reid/models/osnet_x0_25_msmt17.onnx",
-		"C:/work/home/mtracker/tmp/reid/models/osnet_x0_25_msmt17.onnx",
-		cv::Size(128, 256));
-	std::cout << "ec.IsInitialized(): " << ec.IsInitialized() << std::endl;
-
-	cv::Mat img = cv::imread("C:/work/home/mtracker/Multitarget-tracker/build/Release/vlcsnap-2023-10-06-17h31m54s413.png");
-	cv::Rect r1(564, 526, 124, 260);
-	//cv::Rect r2(860, 180, 48, 160);
-	cv::Rect r2(560, 522, 132, 264);
-
-	cv::Mat e1 = ec.Calc(img, r1);
-	cv::Mat e2 = ec.Calc(img, r2);
-
-	//cv::Mat mul = e1 * e2.t();
-	std::cout << "e1: " << e1 << std::endl;
-	std::cout << "e2: " << e2 << std::endl;
-	cv::Mat diff;
-	cv::absdiff(e1, e2, diff);
-	cv::Scalar ss = cv::sum(diff);
-	cv::Mat mul = e1 * e2.t();
-	float res = static_cast<float>(1.f - mul.at<float>(0, 0));
-	std::cout << "mul = " << mul << ", sum = " << ss << ", res = " << res << std::endl;
-
-	cv::rectangle(img, r1, cv::Scalar(255, 0, 255));
-	cv::rectangle(img, r2, cv::Scalar(255, 0, 0));
-	cv::imshow("img", img);
-	cv::waitKey(0);
-
-	return 0;
-#endif
-
     int exampleNum = parser.get<int>("example");
     int asyncPipeline = parser.get<int>("async");
 
diff --git a/src/Tracker/Ctracker.cpp b/src/Tracker/Ctracker.cpp
index 0fea8ca5..f93b8d1a 100644
--- a/src/Tracker/Ctracker.cpp
+++ b/src/Tracker/Ctracker.cpp
@@ -233,7 +233,7 @@ void CTracker::UpdateTrackingState(const regions_t& regions,
         std::cout << "CTracker::UpdateTrackingState: Distance matrix between all tracks to all regions" << std::endl;
 #endif
         distMatrix_t costMatrix(N * M);
-        const track_t maxPossibleCost = static_cast<track_t>(currFrame.cols * currFrame.rows);
+        const track_t maxPossibleCost = std::max(static_cast<track_t>(1.), static_cast<track_t>(currFrame.cols * currFrame.rows));
         track_t maxCost = 0;
         CreateDistaceMatrix(regions, regionEmbeddings, costMatrix, maxPossibleCost, maxCost);
 #if DRAW_DBG_ASSIGNMENT