Sketch recognition based on manifold learning

Authors:
Heeyoul Choi;Tracy Hammond
Affiliations:
Department of Computer Science, Texas A&M University, College Station, TX;Department of Computer Science, Texas A&M University, College Station, TX
Venue:
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Year:
2008

Citing 3
Cited 0

Specifying gestures by example

Proceedings of the 18th annual conference on Computer graphics and interactive techniques
Visual similarity of pen gestures

Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Robust kernel Isomap

Pattern Recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

Current feature-based methods for sketch recognition systems rely on human-selected features. Certain machine learning techniques have been found to be good nonhnear features extractors. In this paper, we apply a manifold learning method, kernel Isomap, with a new algorithm for multi-stroke sketch recognition, which significantly outperforms the standard feature-based techniques.