6.801 | Fall 2020 | Undergraduate

Machine Vision

Calendar

Lecture # Topics Key Dates
1 Overview and image formation. Where will it image? How bright will it be? How can we invert image formation? Homework 1 Assigned
2 Image formation, perspective projection, time derivative, and motion field  
3 Time to contact, focus of expansion, direct motion vision methods, and noise gain Homework 2 Assigned
4 Fixed optical flow, optical mouse, constant brightness assumption, and closed form solution  
5 TTC and FOR Montivision demos, vanishing point, and use of VPs in camera calibration Homework 3 Assigned
6 Photometric Stereo, noise Gain, error amplification, eigenvalues, and eigenvectors review  
7 Gradient space, reflectance map, image irradiance equation, and gnomonic projection  
8 Shape from shading in special cases, lunar surface, scanning electron microscope, and Green’s theorem in photometric stereo  
9 Shape from shading in general case—from first order nonlinear PDE to five ODEs Homework 4 Assigned
10 Characteristic strip expansion, shape from shading, and iterative solutions  
11 Edge detection, subpixel position, CORDIC, and line detection (US Patent 6,408,109) Homework 5 Assigned
12 Blob analysis, binary image processing, use of Green’s theorem, and derivative and integral as convolutions  
13 Object detection, recognition and pose determination, and PatQuick (US Patent 7,016,539)  
14 Inspection in PatQuick, Hough transform, homography, position determination, and multi-scale  
15 Alignment, recognition in PatMAx, distance field, and filtering and sub-sampling (US Patent 7,065,262)  
16 Fast convolution, low pass filter approximations, and integral images (US Patent 6,457,032)  
17 Photogrammetry, orientation, axes of inertia, symmetry, and absolute, relative, interior, and exterior orientation  
18 Rotation and how to represent it, unit quaternions, and the space of rotations  
19 Absolute orientation in closed form, outliers and robusteness, and RANSAC  
20 Space of rotations, regular tesselations, and critical surfaces in motion vision and binocular stereo  
21 Relative orientation, binocular stereo, structure from motion, quadrics, camera calibration, and reprojection  
22 Exterior orientation, recovering position and orientation, bundle adjustment, and object shape  
23 Gaussian image and extended Gaussian image, solids of revolution, direction histograms, and regular polyhedra  
24 Putting it all together  

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Fall 2020
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