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Real — time two hand gesture recognition with condensation and hidden Markov models | IEEE Conference Publication | IEEE Xplore

Real — time two hand gesture recognition with condensation and hidden Markov models


Abstract:

This paper presents a technique for two-hand gesture recognition. There are two main processes performed to recognize hands, i.e. hand tracking and gesture cognition. In ...Show More

Abstract:

This paper presents a technique for two-hand gesture recognition. There are two main processes performed to recognize hands, i.e. hand tracking and gesture cognition. In the hand tracking process, a condensation density propagation (Condensation algorithm) is used to localize and track hands (centered at the center of palms) when they are moving. Hidden Markov Model is implemented in recognition part to understand the gestures performed by human. There are 8 gestures used in this study. The experiment is conducted on the collected data (of 8 hand gestures). The results show that the proposed technique provides a promising results, achieving 96.25%.
Date of Conference: 07-09 January 2018
Date Added to IEEE Xplore: 31 May 2018
ISBN Information:
Conference Location: Chiang Mai, Thailand

I. Introduction

With the advanced technology available currently, hand gesture recognition is one of expedient computer vision applications that aimed to perform by in real-time systems [1]. To achieve the task of gesture recognition in video images, image processing and machine learning techniques are involved. The process can be decomposed from a very low-image processing procedures to a high level computation to understand hand gestures. The recognition is to assign a certain class of gesture types to an image extracted from the videos. There are three main processes that have been implemented to recognize hand gestures [1], [2], which are as follows: (1) image acquisition and hand detection, (2) feature extraction and (3) gesture recognition, can be performed by as a classification module that is aimed to classify the gesture into different types.

References

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