
Explore how computer vision, a subfield of artificial intelligence, lets computers see and interpret digital images and videos. Discover its applications across healthcare, automotive, manufacturing, retail, and entertainment.
Learn image filtering and enhancement to improve quality with kernels and pixel transformations. Use smoothing, sharpening, and edge detection, and apply contour stretching, histogram equalization, and gamma correction.
Explore image descriptors and feature matching, including hog, lbp, cnn descriptors, and flann or ransac, to describe regions, compare images, and verify faces.
Explore structure from motion (SFM) and 3D reconstruction by using multiple photographs from different angles to create a 3D scene model, using feature matching, camera pose estimation, and bundle adjustment.
Discover how augmented reality and virtual reality fuse real and virtual worlds using AR glasses, VR headsets, smartphone overlays, markers, and controllers to enhance education, entertainment, tourism, and healthcare.
Explore how computer vision enables robotics and autonomous systems, from autonomous vehicles and drones to humanoid robots that perceive roads, traffic, pedestrians, enabling tasks without human intervention.
Computer vision is the field of study that enables computers to see and understand the visual world. It is one of the most exciting and rapidly evolving areas of artificial intelligence, with applications ranging from face recognition and biometrics to self-driving cars and augmented reality. In this course, you will learn the fundamental concepts and techniques of computer vision, as well as how to apply them to real-world problems.
This course provides a comprehensive introduction to the field of computer vision. It covers the fundamental concepts of image representation and processing, image features and descriptors, image classification and object recognition, motion analysis and tracking, and 3D computer vision.
The course is structured into six modules, each covering a major topic of computer vision. Each module consists of video lectures, quizzes, and assignments. You will not need to write any code in this course, as you will use interactive tools and platforms that allow you to experiment with computer vision algorithms. You will also have access to a rich set of resources, such as readings, code examples, and datasets.
By the end of this course, you will have a solid foundation in computer vision. You will also gain a deeper appreciation of the power and potential of computer vision, as well as its ethical implications and limitations. Whether you want to pursue a career in computer vision, enhance your existing skills, or simply satisfy your curiosity, this course will help you achieve your learning goals.