Yu J., Tao D. Modern Machine Learning Techniques and Their Applications in Cartoon Animation Research

Wiley-IEEE Press, 2013. — 208 p. — ISBN: 1118115147, 9781118115145The integration of machine learning techniques and cartoon animation research is fast becoming a hot topic. This book helps readers learn the latest machine learning techniques, including patch alignment framework; spectral clustering, graph cuts, and convex relaxation; ensemble manifold learning; multiple kernel learning; multiview subspace learning; and multiview distance metric learning. It then presents the applications of these modern machine learning techniques in cartoon animation research. With these techniques, users can efficiently utilize the cartoon materials to generate animations in areas such as virtual reality, video games, animation films, and sport simulationsPerception
Overview of Machine Learning Techniques
Recent Developments in Computer Animation
Chapter Summary
Modern Machine Learning Techniques
A Unified Framework for Manifold Learning
Spectral Clustering and Graph Cut
Ensemble Manifold Learning
Multiple Kernel Learning
Multiview Subspace Learning
Approach Overview
Techinique Details
Multiview Distance Metric Learning
Multi-task Learning
Chapter Summary
Animation Research: A Brief Introduction
Traditional Animation Production
Computer-Assisted Systems
Cartoon Reuse Systems for Animation Synthesis
Graphical Materials Reuse: More Examples
Chapter Summary
Animation Research: Modern Techniques
Automatic Cartoon Generation with Correspondence Construction
Cartoon Characters Represented by Multiple Features
Graph-based Cartoon Clips Synthesis
Retrieval-based Cartoon Clips Synthesis
Chapter Summary