How to detect faces in images using the appearance-based method and the Neural Networks?
How to detect faces in videos?
Learn what images and pixels are and how to access and manipulate them using OpenCV
Learn how to load camera frames and video files and how to create some simple video animations
In this post we are going to explain how to draw basic and more advanced shapes, as well as how to write text on images
In this post, we’ll cover basic image transformations like image resizing, image translation, image rotation and image flipping
Learn how to blur and sharpen images and how to create instagram like filters
Learn how to perform some elementary arithmetic operations on images like addition and subtraction
Learn how to combine dilation and erosion to create more advanced image operations
Learn how we can apply machine learning theory on the pixel intensity color with the K-means clustering algorithm
Learn the theory behind the Haar cascade classifiers, and learn how to use them to detect faces, eyes and smiles with OpenCV in Python
Learn how to detect facial landmarks in an image using dlib and OpenCV
Face alignment is one important step that we need to master before we start to work on some more complicated image processing tasks
Learn how to develop a computer vision application that is capable of detecting and counting eye blinks in videos
A fun and interesting way to blend and paste images on top of each other
Learn how to estimate the motion of every pixel in a video sequence by using the Optical Flow method
Learn to detect moving objects in a video using the Lucas Kanade method
Learn to identify the parts of an image that match a predefined template
Learn to match distinctive features in images by using Brute-force and FLANN based feature matching methods
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