This course is taught by Computer Vision expert from University of Edinberg. The course is implementation oriented and less of theorey. If you do not care about the theorey and are looking for a quick implememntation guide on popular OpenCV algorithms, this is the course to take.
- Key concepts of computer Vision & OpenCV.
- Perform image manipulations such as transformations, cropping, blurring, thresholding, edge detection and cropping.
- Segment images by understanding contours, circle, and line detection. How to approximate contours, do contour filtering and ordering as well as approximations.
- Feature detection (SIFT, SURF, FAST, BRIEF & ORB) for object detection.
- Implement Object Detection for faces, people & cars.
- Extract facial landmarks for face analysis, applying filters and face swaps.
- Implement Machine Learning in Computer Vision for handwritten digit recognition.
- Implement Facial Recognition.
- Implement and understand Motion Analysis & Object Tracking.
- Use basic computational photography techniques for Photo Restoration (eliminate marks, lines, creases, and smudges from old damaged photos).
- Getting started in Deep Learning.
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Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent