Title :
Gesture recognition system based on Adaptive Resonance Theory
Author :
Park, Paul K. J. ; Jun Haeng Lee ; Chang Woo Shin ; Hyun-Surk Ryu ; Byung-Chang Kang ; Carpenter, G.A. ; Grossberg, Stephen
Author_Institution :
Frontier IT Lab., Samsung Adv. Inst. of Technol., Yongin, South Korea
Abstract :
We report on the moving hand gesture recognition technique using Adaptive Resonance Theory (ART). To detect the start and end points of a continuous moving gesture (known as “gesture spotting” problem), we propose the adaptive distributed prediction technique. Our results show that, unlike conventional non-recurrent neural networks, the proposed technique can be utilized usefully in reliable real-time learning (2000 times faster than with alternative methods) and recognition of continuously moving patterns.
Keywords :
adaptive resonance theory; gesture recognition; learning (artificial intelligence); prediction theory; ART; adaptive distributed prediction technique; adaptive resonance theory; continuous moving gesture end point detection; continuous moving gesture start point detection; continuously moving patterns; gesture spotting problem; moving hand gesture recognition technique; nonrecurrent neural networks; reliable real-time learning; Adaptive systems; Feature extraction; Gesture recognition; Humans; Subspace constraints; Vectors;
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
Print_ISBN :
978-1-4673-2216-4
