Book Image

Mastering OpenCV 4 - Third Edition

By : Roy Shilkrot, David Millán Escrivá
Book Image

Mastering OpenCV 4 - Third Edition

By: Roy Shilkrot, David Millán Escrivá

Overview of this book

Mastering OpenCV, now in its third edition, targets computer vision engineers taking their first steps toward mastering OpenCV. Keeping the mathematical formulations to a solid but bare minimum, the book delivers complete projects from ideation to running code, targeting current hot topics in computer vision such as face recognition, landmark detection and pose estimation, and number recognition with deep convolutional networks. You’ll learn from experienced OpenCV experts how to implement computer vision products and projects both in academia and industry in a comfortable package. You’ll get acquainted with API functionality and gain insights into design choices in a complete computer vision project. You’ll also go beyond the basics of computer vision to implement solutions for complex image processing projects. By the end of the book, you will have created various working prototypes with the help of projects in the book and be well versed with the new features of OpenCV4.
Table of Contents (12 chapters)

Theory and context

Facial landmark detection algorithms automatically find the locations of key landmark points on facial images. Those key points are usually prominent points locating a facial component, such as eye corner or mouth corner, to achieve a higher-level understanding of the face shape. To detect a decent range of facial expressions, for example, points around the jawline, mouth, eyes, and eyebrows are needed. Finding facial landmarks proves to be a difficult task for a variety of reasons: great variation between subjects, illumination conditions, and occlusions. To that end, computer vision researchers proposed dozens of landmark detection algorithms over the past three decades.

A recent survey of facial landmark detection (Wu and Ji, 2018) suggests separating landmark detectors into three groups: holistic methods, constrained local model (CLM) methods, and regression...