Title :
Static hand sign recognition using linear projection methods
Author :
Gamage, Nuwan ; Chow, Kuang Ye ; Akmeliawati, Rini
Author_Institution :
Dept. of Electr. & Comput. Syst. Eng., Monash Univ., Bandar Sunway
Abstract :
Shape matching is one of the more significant research topics in the fields of computer vision, pattern recognition and machine learning. Successful shape matching algorithms/ methods has a high potential for a wide variety of practical applications. In this paper, we present our effort on using linear projection methods for static hand sign recognition in Malaysian sign language. PCA and LPP methods have been used with a database of 240 hand shapes.
Keywords :
image matching; object recognition; principal component analysis; Malaysian sign language; PCA methods; computer vision; linear projection methods; locality preserving projections; machine learning; pattern recognition; principal component analysis; shape matching algorithms; static hand sign recognition; Application software; Computer vision; Databases; Handicapped aids; Machine learning; Machine learning algorithms; Pattern matching; Pattern recognition; Principal component analysis; Shape; LPP; PCA; hand signs; shape matching;
Conference_Titel :
Autonomous Robots and Agents, 2009. ICARA 2009. 4th International Conference on
Conference_Location :
Wellington
Print_ISBN :
978-1-4244-2712-3
Electronic_ISBN :
978-1-4244-2713-0
DOI :
10.1109/ICARA.2000.4803982
