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Portofolio Mata Kuliah Computer Vision 1819


1. Introduction to computer vision. [Slide]

Image Formation and Filtering
2. Cameras and optics. [Slide]
3. Light and color. [Slide]
4. Image filtering. [Slide]
5. Thinking in frequency. [Slide]
6. Image pyramids and applications. [Slide]

Feature Detection and Matching
7. Edge detection. [Slide]
8. Interest points and corners. [Slide]
9. Local image features. [Slide]
10. Feature matching and hough transform. [Slide]
11. Model fitting and RANSAC. [Slide]

Multiple Views and Motion
12. Stereo. [Slide]
13. Epipolar Geometry and Structure from Motion. [Slide]
14. Feature Tracking and Optical Flow. [Slide]


1. http://cs.brown.edu/courses/cs143/
2. http://szeliski.org/Book/
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