Yihsin Ho, T. Nishitani, Toru Yamaguchi, E. Sato-Shimokawara, N. Tagawa
{"title":"A Hand Gesture Recognition System Based on GMM Method for Human-Robot Interface","authors":"Yihsin Ho, T. Nishitani, Toru Yamaguchi, E. Sato-Shimokawara, N. Tagawa","doi":"10.1109/RVSP.2013.72","DOIUrl":null,"url":null,"abstract":"This paper proposes a hand gesture recognition system for human-robot interface. Our research aims to provide users user-friendly operations in a more intuitive manner. We use the stereo camera to capture images as the primary source of information retrieval, and adapt Gaussian mixture model (GMM) method as the main method of image analysis. The GMM method we applied in this paper is a precise, stable and computationally efficient foreground segment method. Our system is mainly with the following three steps: take video by camera, obtain user's images based on GMM method, and recognize hand gesture. In this paper, we will focus on describing the system's overall concepts and GMM method. An experiment result of our prototype will also be discussed to show the research potential of our system.","PeriodicalId":6585,"journal":{"name":"2013 Second International Conference on Robot, Vision and Signal Processing","volume":"35 1","pages":"291-294"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Second International Conference on Robot, Vision and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RVSP.2013.72","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper proposes a hand gesture recognition system for human-robot interface. Our research aims to provide users user-friendly operations in a more intuitive manner. We use the stereo camera to capture images as the primary source of information retrieval, and adapt Gaussian mixture model (GMM) method as the main method of image analysis. The GMM method we applied in this paper is a precise, stable and computationally efficient foreground segment method. Our system is mainly with the following three steps: take video by camera, obtain user's images based on GMM method, and recognize hand gesture. In this paper, we will focus on describing the system's overall concepts and GMM method. An experiment result of our prototype will also be discussed to show the research potential of our system.