Computer Vision in Sommer Term 2021
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Topics
- Image formation
- Image processing
- Feature detection and matching
- Segmentation
- Shape from X
Prerequisites
- Calculus and linear algebra
- Basic knowledge in computergraphics would be helpful
Documents
- Slides of lecture 1, Assignment 1, covtest.dat
- Slides of lecture 2, Assignment 2, calibrationImagesCheckerboard.zip
- Slides of lecture 3, Assignment 3
- Slides of lecture 4, Assignment 4, koreanSigns.png
- Slides of lecture 5, Assignment 5, Church.zip
- Slides of lecture 6, Assignment 6, quadrotor.mp4
- Slides of lecture 7, Assignment 7, Ellipsoids.zip, bunnyImages.zip, buddaImages.zip
- Slides of lecture 8, Assignment 8, squirrel_images_and_data.zip
- Slides of lecture 9, Assignment 9
- Slides of lecture 10, Assignment 10, SfMVideos1.zip, SfMVideos2.zip
- Slides of lecture 11, Assignment 11
- Slides of lecture 12
References
- Ma, Y.; Soatto, S.; Kosecke, J.; Sastry, S. S.; An Invitation to 3-D Vision, Springer, 2004
- Forsyth, D.; Ponce, J.; Computer Vision. A Modern Approach, Prentice Hall, 2003
- Hartley, R.; Zisserman, A.; Multiple View Geometry in Computer Vision, Cambridge University Press, 2003
- Bradski, G.; Kaehler, A.; Learning OpenCV: Computer Vision with the OpenCV Library, O’Reilly Media, 2008
- Lélis Baggio, D.; Emami, S.; Millán Escrivá, D.; Ievgen, K.; Mahmood, N.; Saragih, J.; Shilkrot, R.; Mastering OpenCV with Practical Computer Vision Projects, Packt Publishing, 2012
- Laganiére, R.; OpenCV 2 Computer Vision Application Programming Cookbook, Packt Publishing, 2011
- Szeliski, R.; Computer Vision: Algorithms and Applications, Springer, 2010 (http://szeliski.org/Book/)