We already learned what facial landmarks are and how to detect them. Now we are ready to expand that knowledge and put it into the practice to solve other similar problems. In this post we are going to explain how we can detect and count eye blinking in videos. To develop an eye blinking detector, we need to detect facial landmarks of the eyes, and then we need to calculate the aspect ratio between these…
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Highlight: In this post we are going to demonstrate how to apply face alignment using OpenCV and Python. Face alignment is one important step that we need to master before we start to work on some more complicated image processing tasks in Python. So, let’s see what face alignment is and why this method is necessary if we want to achieve higher accuracy in face recognition algorithms. Tutorial Overview: What is face alignment? Face alignment…
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Highlight: In this post you are going to learn how to detect facial landmarks in an image using dlib and OpenCV. This knowledge will be useful, since facial landmarks are the key features in a large number of facial analysis methods and algorithms. Face recognition, face alignment, facial expression recognition, face swapping, drowsiness detection, blink detection, head pose estimation, are the few examples in which facial landmarks play a fundamental role. let us see what…
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Highlights: If you have any type of camera that does face detection it is probably using Haar feature-based cascade classifier for object detection. In this post we are going to learn what are these Haar cascade classifiers and how to use them to detect faces, eyes and smiles. Tutorial Overview: Understanding Haar cascade classifiers How to detect faces, eyes and smiles with Haar cascade classifiers? 1. Understanding Haar Cascade Classifiers Two decades ago, face detection…
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Highlight: In this OpenCV with Python post we are going to talk about morphological transformations. Fundamentally, there are two basic morphological transformations and they are called dilation and erosion. They are present in image processing in different applications. They are used for the removal of noise or for finding the bumps or holes in images. In addition, these operations can also be used to calculate gradients of images. Moreover, once we learn two basic morphological…
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