Advanced 2D computer graphics - current information (2017/2018)

Lecture: every WEDNESDAY AT 15:40 in SU2 lab (Malá Strana)

Labs: every other THURSDAY AT 12:20 (12. 10. and then regularly from 19. 10. 2017) in the SW2 lab.

Lecture plan

Lecture #1 (4. 10. 2017)

Introduction, literature, image transparency and composition using alpha-channel

Alpha channel, unary and binary operators, examples. Introduction to image warping.

Lecture #2 (11. 10. 2017)

Image warping

Image warping: forward/backward computation, interpolation and filtering, MIP-map, multi-pass methods. Concrete definitions of deformation mappings: triangle mesh, quad mesh, B-spline deformation, two-pass spline method.

Lab #1 (12. 10. 2017)

Credit system, tasks, programming environment (C# language, SVN repository, MS Visual Studio).

Task 080: Triangle mesh warping
Task 074: Demo program for alpha-blending

Lecture #3 (18. 10. 2017)

Warping - deformations, Morphing

Warping methods: feature-based warping. Image morphing: principles, Temporal interpolation of deformation mapping, problems, shape metamorphosis using physics (planar polygon blending).
A Physically Based Approach to 2D Shape Blending by Sederbergh and Greenwood.

Lab #2 (19. 10. 2017)

Examples: warping, morphing.

Task 076: Demo program for 0D feature warping

Lecture #4 (25. 10. 2017)

Spatial data structures I

Applications, data types, elementary tasks, Region-quadtree, Pyramid, MX-quadtree, PR-quadtree, bucket PR-quadtree, Point-quadtree (delete), KD-tree, adaptive KD-tree, BSP tree, 'range tree' and interval queries in 1D and 2D

Lecture #5 (1. 11. 2017)

Spatial data structures II, collision detection

R-tree, Strip tree, PMx quadtree (1,2,3,R), generic geometry-based pass through general hierarchy (using a heap), collision detection, BVH, hierarchy efficiency

Lab #3 (2. 11. 2017)

Applets for spatial data structures (František Brabec). Point placement in 2D (CCPD, Mitchell, 077mitchell).

Task 111: Efficient kNN search in 2D

Lecture #7 (15. 11. 2017)

Introduction to image compression

Image compression: basic ideas, applications, genealogy. Basic terms (entropy, entropic coding), compression requirements, lossy vs. losless compression.

Lab #4 (16. 11. 2017)

Prediction in text compression, entropic codecs, API for entropic compression in C#

Task 011: Lossless compression of B/W image

Lecture #8 (22. 11. 2017)

Image compression - predictive methods, transform coding

Channel coding: PCM, quantization, DM, Lloyd-Max quantizer, predictive methods (DPCM), 2D DPCM, adaptive prediction methods General transform compression, block quantization, Karhunen-Loeve transform, hybrid methods, interpolation compression (alternating interpolation), coefficient coding: zonal and threshold methods, adaptive transform coding

Lecture #9 (29. 11. 2017)

Image compression - orthogonal systems

Suboptimal (actually used in practice) orthogonal systems: Fourier series, Fourier transform, DFT, fast DFT (FFT), DST, DCT, Rademacher basis, Hadamard and Walsh bases, fast algorithms, Haar wavelet (wavelet for dummies)


Copyright (C) 2001-2017 J.Pelikán, last change: 2017-11-16 02:38:31 +0100 (Thu, 16 Nov 2017)