Shape Design, Johnstone, Spring 2007
Lecture notesM. Pollefeys and L. Van Gool. From Images to 3D Models, Communications of the ACM, July 2002/Vol. 45, No. 7, pp.50-55.
Chapter 2 images from Hartley and Zisserman, Multiple View Geometry in Computer Vision. (Figures 4a, 6b, 6c, 13a and 18a are of most interest for testing of HW1).
How to convert an image to ppm/pgm format
OpenGL Programming Guide online resource, Version 1.1 (longterm, I recommend buying the latest edition from Addison-Wesley; also look around opengl.org for discussion of GLUT)
2D OpenGL/GLUT template C++ file
3D OpenGL/GLUT template C++ file
glut.h (old version in case you can't get your hands on it): put this in /usr/include/GL; you are also free to use non-GLUT alternatives (please let me know your experiences and favourites)
OpenCV demo #1: open and display an image
OpenCV demo #2: accept mouse input to edit an image
OpenCV demo #3: resize the window containing an image
OpenCV demo #4: pixel manipulation
OpenCV demo #5 (very short): image output
Makefile for OpenCV demos (make sure to change its name to Makefile)
Installation notes for CLAPACK
CLAPACK demo #1: solving Ax=b with LU decomposition
Structure from motion seminar, Johnstone, Spring 2007, UAB CIS
Research papersOlivier Faugeras. What can be seen in three dimensions with an uncalibrated stereo rig?, European Conference on Computer Vision, 1992, 563-578. (projective reconstruction)
R. Hartley, R. Gupta, and T. Chang. Stereo from Uncalibrated Cameras, CVPR 1992, 761-764. (projective reconstruction)
Marc Pollefeys, Reinhard Koch, and Luc Van Gool, Self-Calibration and Metric Reconstruction in spite of Varying and Unknown Internal Camera Parameters, ICCV '98, 90-95. (calibration for metric reconstruction)
Andrew Fitzgibbon and Andrew Zisserman. Automatic Camera Recovery for Closed or Open Image Sequences, ECCV98.
M. Prasad, A. Zisserman and A. Fitzgibbon. Single view reconstruction of curved surfaces, CVPR06.
A. Criminisi, I. Reid, A. Zisserman. Single View Metrology, ICCV99, 434-442.
Structure from motion seminar, Johnstone, Fall 2006, UAB CIS
Research papersDavid Marr, Vision (Freeman, 1983). (theory of feature detection)
Linda Shapiro and George Stockman, Computer Vision (general reference such as Gaussian filters, derivative masks)
David G. Lowe, "Distinctive image features from scale-invariant keypoints," International Journal of Computer Vision, 60, 2 (2004), pp. 91-110. (SIFT; feature extraction and matching)
Jeffrey S. Beis and David G. Lowe, "Shape indexing using approximate nearest-neighbour search in high-dimensional spaces," Conference on Computer Vision and Pattern Recognition, Puerto Rico (June 1997), pp. 1000-1006. (BBF = best-bin first; matching)
Krystian Mikolajczyk, "Detection of local features invariant to affine transformations" PhD thesis, INRIA Rhone-Alpes, 2002.
Sourceforge documentation of ppm image format
David Lowe, SIFT software.
Software for Mikolajczyk and Schmid affine covariant region detection
H.C. Longuet-Higgins, 'A computer algorithm for reconstructing a scene from two projections', Nature, Vol. 293, pp. 133-135. (computation of the essential matrix, a special form of the fundamental matrix)
M. Fischler and R. Bolles, 'Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography', CACM 24(6), June 1981, pp. 381--395. (RANSAC)
Richard Hartley and Andrew Zisserman, Multiple View Geometry in Computer Vision (Cambridge University Press, 2004).
Paul Debevec, Camillo Taylor and Jitendra Malik, Modeling and Rendering Architecture from Photographs: A hybrid geometry and image-based approach. SIGGRAPH 1996, 11-20.
SIGGRAPH 2000 Course on 3D Photography
Download OpenCV Library (also see tutorials under 'Files')
Microsoft Research Phototourism
The Computer Vision Homepage (hosted by CMU)
Computer Vision Software, part of The Computer Vision Homepage (CMU)
Annotated Computer Vision Bibliography (maintained by Keith Price at USC)
Image data from Oxford Visual Geometry Group
Peter Kovesi MATLAB functions (including projective geometry, fundamental matrix, fitting, ...)
Image-Based Modeling SIGGRAPH 99 course
INRIA Rhones-Alpes vision group
Terence Tao (Fields medal winner), including interesting applets
Haralick and Shapiro 'Robot and Computer Vision' text