Using Principal Component Analysis and Hidden Markov Model for Hand Recognition Systems

Autor:	Luqman Al-Hakim Zainal Abidin, Abdullah Bade, Abd. Manan Ahmad
Rok vydání:	2009
Předmět:	Pixel Computer science business.industry Gesture recognition Principal component analysis Pattern recognition Artificial intelligence Hidden Markov model Machine learning computer.software_genre business computer Gesture
Zdroj:	2009 International Conference on Information and Multimedia Technology.
Popis:	There are many approaches and algorithms that can be used to recognize and synthesize the hands gesture. Each approach has its own advantages and characteristics. This paper describes the usage of Hidden Markov Models (HMM) and Principal Component Analysis (PCA) in recognizing hands gesture by two different researches. The limitations of each techniques and comparisons between each other will be detailed below.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::0bf63336d7d8ad06b11429bf0818e84b https://doi.org/10.1109/icimt.2009.109 Zobrazit plný text záznamu