Vision Based Gesture Recognition for Alphabetical Hand Gestures Using the SVM Classifier

Abstract

In this paper we discuss how a Gesture Recognition system for Alphabetical Hand Gestures is built. The main motive was to develop a system that can simplify the way humans interact with computers. The system is designed using the Support Vector Machine (SVM) Classifier which is widely used for classification and regression testing. SVM training algorithm builds a model that predicts whether a new example falls into one category or other. And the SVM classifier learns from the data points in examples when they are classified belonging to their respective categories.

Authors and Affiliations

Aseema Sultana , T Rajapuspha

Keywords

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  • EP ID EP124998
  • DOI -
  • Views 87
  • Downloads 0

How To Cite

Aseema Sultana, T Rajapuspha (2012). Vision Based Gesture Recognition for Alphabetical Hand Gestures Using the SVM Classifier. International Journal of Computer Science & Engineering Technology, 3(7), 218-223. https://europub.co.uk/articles/-A-124998