Title :
3D Arabic sign language recognition using linear combination of multiple 2D views
Author :
Tolba, M.F ; Samir, Ahmed ; Abul-Ela, Magdy
Author_Institution :
Scientific Computing Department, Faculty of Computer and information Sciences, Ain Shams University; Cairo, Egypt
Abstract :
Earlier researchers in sign language recognition faced a problem in some signs because of the single view based recognition. A model is proposed and developed for multiple-views hand postures recognition. Pulse Coupled Neural Network is used to generate features vector for single view. Two views with different view angles are used; each view generates its features vector. The two 2D-vectors then are linearly combined with weights to produce 3D features which will be used in recognition
Keywords :
IEEE Xplore; Portable document format; 3D object recognition; Arabic Sign Language (ASL); Puke Coupled Neural Network (PCNN); dynamic gesture; static posture;
Conference_Titel :
Informatics and Systems (INFOS), 2012 8th International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4673-0828-1
