Hand gesture recognition using hidden markov models: a review on techniques and approaches

• Main Authors: Mohd. Salleh, Noor Saliza, Jais, Jamilin, Mazalan, Lucyantie, Ismail, Roslan, Yussof, Salman, Ahmad, Azhana, Anuar, Adzly, Mohamad, Dzulkifli
• Format: Conference or Workshop Item
• Language: English
• Published: 2006
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/3057/1/Noor_Saliza_%28edited%29.doc; http://eprints.utm.my/id/eprint/3057/
• Institution: Universiti Teknologi Malaysia

Many ways of communications are used between human and computer, while using gesture is considered to be one of the most natural ways in a virtual reality system. Hand gesture is one of the typical methods of non-verbal communication for human beings and we naturally use various gestures to express our own intentions in everyday life. Gesture recognizers are supposed to capture and analyze the information transmitted by the hands of a person who communicates in sign language. This is a prerequisite for automatic sign-to-spoken-language translation, which has the potential to support the integration of deaf people into society. This paper present part of literature review on ongoing research and findings on different technique and approaches in gesture recognition using Hidden Markov Models for vision-based approach.