Computer Vision: Algorithms & Applications (Czeliski)
Geometric primitives, Photometric image formation, Digital cameras
Point operators, Linear filtering, More neighborhood operators, Fourier transforms, Pyramids & wavelets, Geometric transforms, Global optimization
Points & patches, Edges, Lines
Active contours, Split & merge, Mean shift & mode finding, Normalized cuts Graph cuts & energy-based methods
2D & 3D alignment, Post estimation, Geometric intrinsic calibration
Triangulation, 2-frame structure from motion, Factorization, Bundle adjustment, Constrained structure & motion
Translational alignment, Parametric motion, Spline-based motion, Optical flow, Layered motion
Motion models, Global alignment, Compositing
Photometric calibration, High dynamic range imaging, Super-resolution & blur removal, Image matting & compositing, Texture analysis & synthesis
Epipolar geometry, Sparse correspondence, Local methods, Global optimization, Multi-view stereo
Shapes from X, Active rangefinding, Surface representations, Point-based representations, Volumetric representations, Model-based reconstruction, Recovering texture maps
View interpolation, Layered depth images, Light fields & lumigraphs, Environment mattes, Video-based rendering
Object detection, Face recognition, Instance recognition, Category recognition, Context & scene understanding, Recognition databases
Linear Algebra / Numerical Techniques
Matrix decomposition, Linear least squares, Nonlinear least squares, Direct sparse matrix techniques Interative techniques
Estimation theory, Max likelihood estimation, Robust statistics, Prior models, Markov random fields, Uncertainty estimation