Hand Posture Recognition Using Kernel Descriptor | Zendy

Van-Toi Nguyen | Zendy; ThiLan Le | Zendy; Thanh-Hai Tran | Zendy; Rémy Mullot | Zendy; Vincent Courboulay | Zendy

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Hand Posture Recognition Using Kernel Descriptor

Author(s) -

Van-Toi Nguyen,

ThiLan Le,

Thanh-Hai Tran,

Rémy Mullot,

Vincent Courboulay

Publication year - 2014

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2014.11.023

Subject(s) - kernel (algebra) , artificial intelligence , computer science , rgb color model , pattern recognition (psychology) , computer vision , color space , representation (politics) , mathematics , image (mathematics) , combinatorics , politics , political science , law

In this paper, we propose to investigate the role of a new descriptor named Kernel Descriptor (KDES), recently introduced in1 for hand posture recognition. As the hand posture has it own the color characteristic, we will examine kernel descriptor in diffident color channels such as HSV, RGB, Lab to find out the most suitable color space for kernel representation of hand posture. We perform extensive experiments on two datasets. The obtained results are promising (97.3% on NUS-2 dataset and 85.0% on our dataset). Thank to the analysis, kernel descriptor is highly recommended for hand posture recognition

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