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  <front>
    <journal-meta>
      <journal-title-group><journal-title>SET Proceedings</journal-title></journal-title-group>
      <issn pub-type="epub">2978-4387</issn>
      <publisher><publisher-name>Caravel Press</publisher-name></publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.65582/set.2018.157</article-id>
      <article-id pub-id-type="publisher-id">2018.157</article-id>
      <title-group><article-title>Human-machine interaction intention recognition technology based on D-S evidence theory</article-title></title-group>
    <contrib-group>
      <contrib contrib-type="author">
        <name><surname>Zhang</surname><given-names>Xueyuan</given-names></name>
        <xref ref-type="aff" rid="aff1"/>
        <email>328040576@qq.com</email>
      </contrib>
      <contrib contrib-type="author">
        <name><surname>Yu</surname><given-names>Liping</given-names></name>
        <xref ref-type="aff" rid="aff1"/>
        <email>523182137@qq.com</email>
      </contrib>
      <contrib contrib-type="author">
        <name><surname>Liu</surname><given-names>Ge</given-names></name>
        <xref ref-type="aff" rid="aff1"/>
        <email>646605009@qq.com</email>
      </contrib>
      <contrib contrib-type="author">
        <name><surname>Zhao</surname><given-names>Di</given-names></name>
        <xref ref-type="aff" rid="aff1"/>
        <email>zhd_hbut@126.com</email>
      </contrib>
      <aff id="aff1">School of Mechanical Engineering, HBUT, Wuhan</aff>
    </contrib-group>
      <pub-date publication-format="electronic" date-type="pub"><day>28</day><month>02</month><year>2019</year></pub-date>
      <volume>17</volume>
      <issue>3</issue>
      <isbn publication-format="electronic">978-0-85358-327-1</isbn>
      <fpage>276</fpage>
      <lpage>284</lpage>
      <self-uri xlink:href="https://caravelpress.com/proceedings/set/papers/2018.157"/>
      <history>
        <date date-type="received"><string-date>28 February 2019</string-date></date>
      </history>
      <permissions>
        <copyright-statement>© 2018 Copyright WSSET</copyright-statement>
        <copyright-year>2019</copyright-year>
      </permissions>
      <abstract><p>Human intention recognition plays an important role in human-machine collaboration. In this paper, the intention recognition method for target capture is studied, a vision based method is used in the human-computer interaction, and the trajectory of the body's upper extremity is taken as the main criterion. The user interaction intention model is established by using the multi-dimension judging factor. Then the target fast judging algorithm is optimised by adopted the D-S theory to realize the intention factor fusion. Experiment results show that the intention-identification method proposed in this paper can quickly and accurately identify the operator's grasping intentions and serve human-computer collaboration. The comparison experiments show that the multi-dimensional factor intention identification method is more accurate and more effective than the single factor method.</p></abstract>
      <kwd-group kwd-group-type="author">
        <kwd>Intention recognition</kwd>
        <kwd>D-S theory</kwd>
        <kwd>machine vision</kwd>
        <kwd>human-robot collaboration</kwd>
      </kwd-group>
      <conference>
        <conf-date>21 to 23 August 2018</conf-date>
        <conf-name>17th International Conference on Sustainable Energy Technologies</conf-name>
        <conf-acronym>SET2018</conf-acronym>
        <conf-num>17</conf-num>
        <conf-loc>Wuhan, China</conf-loc>
      </conference>
    </article-meta>
  </front>
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