CASTER/index.html at master · lasso-sustech/CASTER · GitHub

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  <section class="hero">
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            <h1 class="title is-1 publication-title">CASTER: A Computer-Vision-Assisted Wireless
              Channel Simulator for Gesture Recognition</h1>
            <div class="is-size-5 publication-authors">
              <!-- Paper authors -->
              <span class="author-block">
                <a href="https://renzhenyu.site" target="_blank">Zhenyu Ren</a><sup>1</sup>,</span>
                <span class="author-block">
                  Guoliang Li<sup>2</sup>,</span>
                  <span class="author-block">
                    Chenqing Ji<sup>1</sup>,
                  </span>
                  <span class="author-block">
                    Chao Yu<sup>1</sup>,
                  </span>
                  <span class="author-block">
                    <a href="https://bearswang.github.io" target="_blank">Shuai Wang</a><sup>3</sup>,
                  </span>
                  <span class="author-block">
                    <a href="http://lasso.eee.sustech.edu.cn" target="_blank">Rui Wang</a><sup>1,*</sup>
                  </span>
                  </div>

                  <div class="is-size-5 publication-authors">
                    <span class="author-block"><sup>1</sup>Southern University of Science and Technology (SUSTech)
                    <br><sup>2</sup>University of Macau, <sup>3</sup>Chinese Academy of Science
                      <!-- <br>Conference name and year -->
                    </span>
                    <span class="eql-cntrb"><br><sup>*</sup>Corresponding author: Prof. Rui Wang (<a href="mailto:wang.r@sustech.edu.cn">wang.r@sustech.edu.cn</a>)</span>
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</section>


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        <source src="static/videos/hand.mp4"
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      <h2 class="subtitle has-text-centered">
        Hand gesture channel simulation demo with experiment verification.
      </h2>
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        Human motion channel simulation demo with experiment verification (Future Work).
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            <source src="static/videos/hand.mp4"
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          <h2 class="subtitle has-text-centered">
            Hand gesture channel simulation demo with experiment verification using CASTER.
          </h2>
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            Human motion channel simulation demo with experiment verification (Future Work).
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        <h2 class="title is-3">Abstract</h2>
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          <p>
            In this paper, a computer-vision-assisted simulation
            method is proposed to address the issue of training dataset
            acquisition for wireless hand gesture recognition. In the existing
            literature, in order to classify gestures via the wireless channel
            estimation, massive training samples should be measured in
            a consistent environment, consuming significant efforts. In the
            proposed CASTER simulator, however, the training dataset can
            be simulated via existing videos. Particularly, in the channel
            simulation, a gesture is represented by a sequence of snapshots,
            and the channel impulse response of each snapshot is calculated
            via tracing the rays scattered off a primitive-based hand model.
            Moreover, CASTER simulator relies on the existing video clips to
            extract the motion data of gestures. Thus, the massive measurements of wireless channel can be eliminated. The experiments
            first demonstrate an 83.0% average recognition accuracy of
            simulation-to-reality inference in recognizing 5 categories of
            gestures. Moreover, this accuracy can be boosted to 96.5% via
            the method of transfer learning.
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      <!-- Paper video. -->
      <h2 class="title is-3">Real-time gesture recognition demo (in Chinese).</h2>
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            <img src="static/images/simulation_and_exp.png" alt="simulation_and_exp.png""/>
            <h2 class="subtitle has-text-centered">
              Illustration of the simulation (top) and experimental (bottom) setup of CASTER.
            </h2>
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              <img src="static/images/dataset_new2.png" alt="dataset_new2.png"/>
              <h2 class="subtitle has-text-centered">
                This illustration presents both the simulated and experimental datasets derived from CASTER, with a selection of spectrograms depicted for clarity. Our experimental dataset comprises real spectrograms, calculated from received mmWave signals. On the other hand, our simulated dataset is produced by the innovative CASTER simulator. This simulator processes video clips as input, extracts the motion data of gestures, and simulates the channel impulse response for each snapshot by tracing the rays that scatter off a primitive-based hand model. The final step involves applying the Short Time Fourier Transform (STFT) to yield the simulated spectrograms.
              </h2>
            </div>
            <div class="item">
              <img src="static/images/gesture_recognition_result.png" alt="gesture_recognition_result.png"/>
              <h2 class="subtitle has-text-centered">
                Gesture recognition results of CASTER.
              </h2>
              </div>
        </div>
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      Illustration of the simulated and experimental dataset from CASTER, where some examples of spectrogram are plotted.
    </h2>
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<!--BibTex citation -->
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      <h2 class="title">BibTeX citation</h2>
      <pre><code>
        @ARTICLE{10525191,
          author={Ren, Zhenyu and Li, Guoliang and Ji, Chenqing and Yu, Chao and Wang, Shuai and Wang, Rui},
          journal={IEEE Open Journal of the Communications Society},
          title={CASTER: A Computer-Vision-Assisted Wireless Channel Simulator for Gesture Recognition},
          year={2024},
          volume={5},
          number={},
          pages={3185-3195},
          keywords={Videos;Wireless communication;Wireless sensor networks;Gesture recognition;Channel impulse response;Transmitters;Training;Wireless hand gesture recognition;channel model;simulation-to-reality inference},
          doi={10.1109/OJCOMS.2024.3398016}}
      </code></pre>
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</section>
<!--End BibTex citation -->


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