Towards Developing an Effective Hand Gesture Recognition System for Human Computer Interaction: A Literature Survey
Keywords:
hand gesture recognition, neural network (NN), hidden markov model (HMM), support vector machine (SVM), principle component analysis (PCA)
Abstract
Gesture recognition is a mathematical analysis of movement of body parts (hand / face) done with the help of computing device. It helps computers to understand human body language and build a more powerful link between humans and machines. Many research works are developed in the field of hand gesture recognition. Each works have achieved different recognition accuracies with different hand gesture datasets, however most of the firms are having insufficient insight to develop necessary achievements to meet their development in real time datasets. Under such circumstances, it is very essential to have a complete knowledge of recognition methods of hand gesture recognition, its strength and weakness and the development criteria as well. Lots of reports declare its work to be better but a complete relative analysis is lacking in these works. In this paper, we provide a study of representative techniques for hand gesture recognition, recognition methods and also presented a brief introduction about hand gesture recognition. The main objective of this work is to highlight the position of various recognition techniqueswhich can indirectly help in developing new techniques for solving the issues in the hand gesture recognition systems. Moreover we present a concise description about the hand gesture recognition systems recognition methods and the instructions for future research.
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Published
2016-05-15
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Copyright (c) 2016 Authors and Global Journals Private Limited
This work is licensed under a Creative Commons Attribution 4.0 International License.