A guide to expert systems
The nature of statistical learning theory
The nature of statistical learning theory
Learning Visual Models from Shape Contours Using Multiscale Convex/Concave Structure Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human facial illustrations: Creation and psychophysical evaluation
ACM Transactions on Graphics (TOG)
Motion doodles: an interface for sketching character motion
ACM SIGGRAPH 2004 Papers
Mapping learning in eigenspace for harmonious caricature generation
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Prepare to Board! Creating Story and Characters for Animation Features and Shorts
Prepare to Board! Creating Story and Characters for Animation Features and Shorts
Pose-Oblivious Shape Signature
IEEE Transactions on Visualization and Computer Graphics
Apparent ridges for line drawing
ACM SIGGRAPH 2007 papers
Real-time enveloping with rotational regression
ACM SIGGRAPH 2007 papers
Key Point Subspace Acceleration and soft caching
ACM SIGGRAPH 2007 papers
Ontology-based annotation of paintings using transductive inference framework
MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
Shape classification algorithm using support vector machines for traffic sign recognition
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
Shape stylized face caricatures
MMM'11 Proceedings of the 17th international conference on Advances in multimedia modeling - Volume Part I
Sketch based 3D character deformation
Transactions on edutainment V
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Character design is a key ingredient to the success of any comic-book, graphic novel, or animated feature. Artists typically use shape, size and proportion as the first design layer to express role, physicality and personality traits. In this paper, we propose a knowledge mining framework that extracts primitive shape features from finished art, and trains models with labeled metadata attributes. The applications are in shape-based query of character databases as well as label-based generation of basic shape scaffolds, providing an informed starting point for sketching new characters. It paves the way for more intelligent shape indexing of arbitrary well-structured objects in image libraries. Furthermore, it provides an excellent tool for novices and junior artists to learn from the experts. We first describe a novel primitive based shape signature for annotating character body-parts. We then use support vector machine to classify these characters using their body part's shape signature as features. The proposed data transformation is computationally light and yields compact storage. We compare the learning performance of our shape representation with a low-level point feature representation, with substantial improvement.