Video Tutorials (OpenCV 2.4)

A tutorial series contributed by Surya Penmetsa. You can find the codes used in the videos here.

	Tutorial 1: Setup Video This is the first tutorial, where I explain how to install the softwares and get things working to use the OpenCV functions.
	Tutorial 2: Face Detection Video This is the second tutorial, where I explain how to use OpenCV functions to detect faces on MATLAB.
	Tutorial 3: Webcam Input Video This is the third tutorial, where I explain how to use OpenCV functions to record video input on MATLAB.
	Tutorial 4: Feature Extraction and Matching Video This is the fourth tutorial, where I explain how to use OpenCV functions to extract features to match objects on MATLAB.

core: Core Functionality

	Rotated Rectangle The sample demonstrates how to use cv.RotatedRect.
	Reading/Writing XML and YAML files Demonstration of reading/writing from/to XML and YAML file storages.
	Serialization Functionality Demonstrate the usage of OpenCV serialization functionality.
	Image Blending GUI In this demo, we add two images using cv.addWeighted which defines a linear blend operator: $g(x) = (1 - \alpha)f_{0}(x) + \alpha f_{1}(x)$.
	Bitwise Operations on Images In this demo, we show how to perform arithmetic operations on images like addition, subtraction, bitwise operations, etc.
	Brightness and contrast adjustments GUI In this demo we show how to perform the operation: $g(i,j) = \alpha \cdot f(i,j) + \beta$.
	Image padding GUI In this demo, we show how to use the OpenCV function cv.copyMakeBorder to set the borders (extra image padding).
	inRange Thresholding Operations GUI In this demo we show how to perform basic thresholding operations using OpenCV function cv.inRange, and detect an object based on the range of pixel values it has.
	Discrete Fourier Transform This program demonstrated the use of the discrete Fourier transform (DFT). The DFT of an image is taken and it's power spectrum is displayed.
	Kaleidoscope Demonstrates Kaleidoscopic reflections.

imgproc: Image Processing

	Demonstration of drawing functions This program demonstrates OpenCV drawing and text output functions.
	Basic Geometric Drawing In this demo, we show how to use basic drawing functions (line, ellipse, rectangle, circle, etc.).
	Demonstration of text drawing functions Demonstration of text drawing functions.
	Colormaps GUI Sample shows how to apply false color on a grayscale image.
	Delaunay triangulation GUI This program demonstrates iterative construction of Delaunay triangulation and Voronoi tessellation.
	Convex Hull demo GUI We learn how to get hull contours and draw them.
	Retrieve and label connected components from a binary image. The example below shows how to retrieve connected components from a binary image and label them.
	Contours Demo This program illustrates the use of cv.findContours and cv.drawContours.
	Watershed Demo GUI This program demonstrates the famous watershed segmentation algorithm in OpenCV.
	Contours in OpenCV In the sample, we will understand what contours are, and learn about the hierarchy of contours, and how to find and draw contours.
	Finding contours in an image GUI We learn how to find contours of objects in our image.
	Flood-filling in an image GUI An example using the Flood-Fill technique.
	Flood-Fill demo Demonstrates how to use cv.floodFill.
	Image Thresholding In this demo, we will learn about simple thresholding, adaptive thresholding, and Otsu's thresholding.
	Threshold demo GUI Sample code that shows how to use the diverse threshold options offered by OpenCV.
	Smoothing Demo Sample code for simple filters.
	Smoothing Images In this tutorial you will learn how to apply diverse linear filters to smooth images.
	Polar Transforms demo GUI This program illustrates Linear-Polar and Log-Polar image transforms.
	Erosion and Dilation GUI In this sample, you will learn how to apply two very common morphological operators: Erosion and Dilation.
	Advanced Morphology Transformations Demo GUI In this sample you will learn how to use the OpenCV function cv.morphologyEx to apply Advanced Morphological Transformation.
	Extracting horizontal and vertical lines using morphology Example that uses morphology transformations for extracting horizontal and vertical lines.
	Hit-or-Miss Morphological Operation In this tutorial you will learn how to find a given configuration or pattern in a binary image by using the Hit-or-Miss transform.
	Creating Bounding boxes and circles for contours Demo code to find contours in an image, and create bounding boxes and circles.
	Creating Bounding rotated boxes and ellipses for contours Demo code to obtain ellipses and rotated rectangles that contain detected contours.
	Fit ellipses GUI This program is demonstration for ellipse fitting. The program finds contours and approximate them by ellipses.
	Robust Line Fitting GUI Example of using cv.fitLine function for fitting 2D line to points in presence of outliers.
	Image Moments GUI We learn to calculate the moments of an image.
	Gabor Filter demo GUI A GUI to interact with the 5 different Gabor filter parameters, while visualizing the resulting filter.
	Fractalius-like image effect using Gabor filters This sample demonstrates the use of multiple Gabor filter convolutions to get Fractalius-like image effect.
	Line Segment Detector demo An example using the cv.LineSegmentDetector class.
	Hough line detector An example using the Hough line detector.
	Hough circle detector An example using the Hough circle detector.
	Generalized Hough transform This program demonstrates arbitrary object finding with the Generalized Hough transform.
	Interactive foreground extraction using GrabCut GUI Interactive foreground extraction using the GrabCut algorithm.
	Image pyramids for image blending Learn about image pyramids and how to use them for image blending.
	Laplacian Pyramid Construction and Merging GUI The Laplacian Pyramid as a Compact Image Code.
	Image Warping GUI This program shows perspective transformation applied on an image.
	Interactive Perspective Transformation GUI This program demonstrates Perspective Transformation.
	Image Alignment using ECC algorithm This sample demonstrates the use of the ECC image alignment algorithm.
	Corner Detection In this demo we will understand concepts behind Harris Corner Detection. We also learn about another corner detector, the Shi-Tomasi Corner Detector.
	Refining Corner Locations GUI Demo code for detecting corners using Shi-Tomasi method and refining corner locations.
	Template Matching This program demonstrates template match with mask.
	Phase Correlation GUI Demonstrates estimating translational shift between two successive frames using Phase Correlation.
	Convex Hull This sample program demonstrates the use of the cv.convexHull function.
	Minimum Area Enclosing This program demonstrates finding the minimum enclosing box, triangle or circle of a set of points.
	Connected Components GUI This sample demonstrates connected components labeling.
	Canny Edge Detection GUI This sample demonstrates Canny edge detection.
	Laplacian Edge Detection GUI This program demonstrates Laplace point/edge detection using OpenCV function cv.Laplacian.
	Create Binary Mask Interactively GUI Interactively create a polygon mask.
	Create Binary Mask Interactively (IPT) Interactively create a polygon mask.
	Interactive Rectangle Selection Select a rectangle by drawing a box using the mouse, using RectSelector helper class.
	Distance Transform GUI Program to demonstrate the use of the distance transform function between edge images.
	Intensity Image Histogram GUI This program demonstrates the use of cv.calcHist for histogram creation.
	Histogram Calculation In this demo, we show how to divide an image into its correspondent planes and calculate histograms of arrays of images.
	Histogram Equalization In this demo, we show what an image histogram is and why it is useful.
	Histogram Comparison In this demo, we show how to use the function cv.compareHist to get a numerical parameter that express how well two histograms match with each other.
	2D Histogram We explain how to create a 2D color histogram.
	Video Histogram GUI Demo to show live histogram of video, both 1D histograms of RGB channels and 2D histogram of Hue-Saturation.
	Back Projection GUI In this demo, we will learn what is Back Projection and why it is useful.
	CAMShift GUI In this demo, we learn about Meanshift and Camshift algorithms to find and track objects in videos.
	Histogram-based face tracker with CAMShift In this demo, we implement a simple face tracker applied on an input video.
	CLAHE (Contrast Limited Adaptive Histogram Equalization) GUI In this demo, we will learn the concepts of histogram equalization and use it to improve the contrast of our images.
	Image Remapping In this demo, we show how to use the OpenCV function cv.remap to implement simple remapping routines.
	Fun with remap Maps a rectangular image into a circle.
	Image Affine Transformation In this demo, we show how to implement simple affine remapping routines.
	Image Pyramids GUI In this demo, we show how to use the functions cv.pyrUp and cv.pyrDown to downsample or upsample a given image.
	Sobel Derivatives In this demo, we show how to calculate the derivatives of an image using the OpenCV functions cv.Sobel and cv.Scharr.
	Laplace Operator In this demo, we show how to use the OpenCV function cv.Laplacian to implement a discrete analog of the Laplacian operator.
	Point Polygon Test In this sample you will learn how to use the OpenCV function cv.pointPolygonTest.
	Points Inside Convex Polygon We define a pentagon and a set of points. Then, determine which points lie inside, outside, or on the edge of the pentagon.
	Image Segmentation with Distance Transform and Watershed Algorithm Sample code showing how to segment overlapping objects using Laplacian filtering, in addition to Watershed and Distance Transformation.
	Wiener Deconvolution for Image Deblurring GUI Sample shows how DFT can be used to perform Weiner deconvolution of an image with user-defined point spread function (PSF).
	Texture flow direction estimation Sample shows how cv.cornerEigenValsAndVecs function can be used to estimate image texture flow direction.
	Coherence-Enhancing Filtering GUI Coherence-Enhancing Shock Filters.
	Multi-Scale Turing Patterns Generator Generate mathematical artwork.
	Hi-Resolution Image Navigation GUI Sample shows how to implement a simple hi-resolution image navigation.
	Squares Detector It loads several images sequentially and tries to find squares in each image.

imgcodecs: Image File Reading and Writing

	Image similarity under lossy compression Similarity measurements (PSNR and SSIM).
	Create PNG image with alpha transparency Sample shows how to create an RGBA image and store it as a PNG file.

videoio: Media I/O

	Video Capture GUI We learn how to capture live stream from camera and display it, while adjusting basic video color properties.
	Creating a video This demo shows how to write video files.
	Synthetic video Demonstrates using VideoSynth classes as stub for cv.VideoCapture.

video: Video Analysis

	Segment objects in Background Subtractor GUI An example using drawContours to clean up a background segmentation result.
	Tracking of rotating point using Kalman filter GUI Tracking of rotating point.
	Dual TV-L1 Optical Flow Optical Flow Estimation using Dual TV-L1 method.
	Farneback Optical Flow GUI This program demonstrates dense optical flow algorithm by Gunnar Farneback.
	Dense Optical Flow GUI Demo shows how to compute the optical flow for all the points in the frame using cv.calcOpticalFlowFarneback.
	Sparse Optical Flow GUI In this demo, we will understand the concepts of optical flow and its estimation using Lucas-Kanade method.
	Lucas-Kanade Sparse Optical Flow GUI Sparse optical flow to track points.
	Lucas-Kanade Optical Flow GUI A demo of Lukas-Kanade optical flow.
	Lucas-Kanade Tracker GUI Lucas-Kanade sparse optical flow demo. Uses cv.goodFeaturesToTrack for track initialization and back-tracking for match verification between frames.
	Lucas-Kanade Homography Tracker GUI Lucas-Kanade sparse optical flow demo. Uses cv.goodFeaturesToTrack for track initialization and back-tracking for match verification between frames. Finds homography between reference and current views.

calib3d: Camera Calibration and 3D Reconstruction

	Collect Calibration Pattern Images This sample is used to take snapshots of a calibration pattern from live webcam. These images can be later used for camera calibration.
	Camera Calibration This example demonstrates camera calibration in OpenCV.
	Pose Estimation In this sample, we learn to exploit calib3d module to create some 3D effects in images from a calibrated camera.
	Stereo Calibration with square chessboard Demonstration of stereo calibration, rectification, and correspondence.
	Stereo Image Matching Example of stereo image matching to produce a disparity map and point cloud generation.
	Epipolar Geometry In this sample we will learn about the basics of multiview geometry, and we see what is epipole, epipolar lines, epipolar constraint etc.

feature2d: 2D Features Framework

	FAST Algorithm for Corner Detection In this demo, we will understand the basics of FAST algorithm to find corners.
	ORB (Oriented FAST and Rotated BRIEF) In this demo, we will see the basics of ORB.
	Feature Matching + Homography to find a known object In this sample, you will use features2d and calib3d to detect an object in a scene.
	Affine invariant feature-based image matching This sample uses the affine transformation space sampling technique, called ASIFT.
	AKAZE local features matching In this demo, we will learn how to use AKAZE local features to detect and match keypoints on two images. We will find keypoints on a pair of images with given homography matrix, match them and count the number of inliers.
	AKAZE and ORB planar tracking In this demo, we will compare AKAZE and ORB local features by using them to find matches between video frames and track object movements.
	Detect, Compute, and Match Descriptors This program demonstrates how to detect, compute, and match descriptors using various algorithms: ORB, BRISK, and AKAZE.
	Blob Detection This program demonstrates how to use BLOB to detect and filter region.
	Maximally Stable Extremal Regions (MSER) This program demonstrates how to use MSER to detect extremal regions.
	Multi-target planar tracking Example of using features2d framework for multiple planar targets tracking in a video using homography matching.
	Feature homography based planar tracking Example of using features2d framework with homography matching for tracking planar objects in a video.
	Planar augmented reality This sample shows an example of augmented reality overlay over a tracked planar object to show its pose in 3D space.
	Correlation-based Tracking using MOSSE Filters Correlation filter based tracking using MOSSE filters (Minimum Output Sum of Squared Error).

objdetect: Object Detection

	Face Detection GUI Here is an example that illustrates how to detect faces in a live video stream.
	Face and Eyes Detection GUI In this demo, we will learn the basics of face detection using Haar Feature-based Cascade Classifiers, and how the same extends for eye detection, etc.
	Facial Features Detection A program to detect facial feature points using Haarcascade classifiers for face, eyes, nose and mouth.
	Smile Detection GUI This program demonstrates the smile detector.
	DBT Face Detection GUI Detection-Based Tracker Face Detector.
	People Detection using HoG GUI This program demonstrates the use of the HoG descriptor using the pre-trained SVM model for people detection.

dnn: Deep Neural Network module

	Deep Neural Network with Caffe models In this tutorial you will learn how to use DNN module for image classification by using GoogLeNet trained network from Caffe model zoo.
	Fully-Convolutional Networks for Semantic Segmentation Fully Convolutional Models for Semantic Segmentation.
	DNN Image Classification Image Classification task using DNN.
	DNN Semantic Segmentation This sample demonstrates semantic segmentation, where we label each pixel in the image with a category label.
	DNN Object Detection This sample uses Single-Shot Detector to detect objects on image (produces bounding boxes and corresponding labels).
	DNN Face Detection Face detector based on SSD framework (Single Shot MultiBox Detector).
	DNN Face Recognition Face detection and recognition based on SSD and OpenFace embedding.
	DNN: Style Transfer Maps the artistic style of various pieces of artwork onto input image.

ml: Machine Learning

	K-Means Clustering This program demonstrates kmeans clustering. It generates an image with random points, then assigns a random number of cluster centers and uses kmeans to move those cluster centers to their representitive location.
	EM Clustering Demonstrates EM clustering.
	Gaussian Mixture Model (GMM) Demonstrates EM clustering, and also compares againt K-means clustering.
	K-Means Color Quantization We will learn how to use cv.kmeans for data clustering of pixels to perform color quantization.
	Comparison of different classifiers on the same dataset This demonstrates an example of machine learning algorithms in a simple classification problem. It compares different classifiers using the same data samples.
	Showcase different classifiers Example using different classifiers.
	Logistic Regression Logistic Regression to classify hand-written digits.
	Support Vector Machines (SVM) In this sample, you will learn how to use the OpenCV function cv.SVM to build a classifier based on SVMs and to test its performance.
	K-Nearest Neighbors (KNN) In this demo, we will understand the concepts of k-Nearest Neighbour (kNN) algorithm, then demonstrate how to use kNN classifier for 2D point classification.
	Principal Component Analysis (PCA) In this demo, you will learn how to use the OpenCV class cv.PCA to calculate the orientation of an object.
	PCA for dimensionality reduction This program demonstrates how to use OpenCV PCA with a specified amount of variance to retain.
	SVMSGD Interactive Classification GUI Train a classifier with SVMSGD algorithm that can handle linearly separable 2-class dataset.
	OCR of hand-written digits using KNN We will use kNN to build a basic OCR application.
	OCR of English letters using KNN We will use kNN to build a basic OCR application.
	OCR of hand-written digits using HoG and SVM In this tutorial, we will build an SVM classifer to recognize hand-written digits (0 to 9), using Histogram of Oriented Gradients (HOG) as feature vectors.

photo: Computational Photography

	High Dynamic Range Imaging In this tutorial we show how to generate and display HDR image from an exposure sequence.
	Inpainting GUI We will learn how to remove small noises, strokes, etc. in old photographs by a method called inpainting.
	Non-Photorealistic Rendering This tutorial demonstrates how to use OpenCV Non-Photorealistic Rendering Module.
	Seamless Cloning This tutorial demonstrates how to use OpenCV seamless cloning module.
	Non-Local Means Image Denoising In this demo, we will learn about Non-local Means Denoising algorithm to remove noise in an image.

stitching: Images Stitching

	Simple rotation model images stitcher A basic example on image stitching.
	Rotation model images stitcher A detailed example on image stitching.

shape: Shape Distance and Matching

Shape context for shape matching This program demonstrates a method for shape comparison based on Shape Context.

superres: Super Resolution

Super Resolution algorithms for video sequence This sample demonstrates Super Resolution algorithms for video sequence.

videostab: Video Stabilization

Video Stabilizer This sample demonstrates video stabilization algorithms for video sequence.