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<p class="MsoNormal" align="left" style="line-height: 12.6pt;"><span lang="EN-US">Personal and Ubiquitous Computing Theme Issue on <o:p></o:p></span></p>
<p class="MsoNormal" style="line-height:12.6pt"><b><span lang="EN-US">Device-Free Sensing for Human
Behavior Recognition</span></b><span lang="EN-US"><o:p></o:p></span></p>
<p class="MsoNormal" style="line-height:12.6pt"><span lang="EN-US"><a href="https://www.facebook.com/personalubicomp" target="_blank">https://www.facebook.com/personalubicomp</a><o:p></o:p></span></p>
<p class="MsoNormal" style="line-height:12.6pt"><b><span lang="EN-US" style="mso-bidi-font-size:10.5pt;color:red">Manuscript Submission: May 1, 2018</span></b><span lang="EN-US"><o:p></o:p></span></p>
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<p class="MsoNormal"><span lang="EN-US"> </span></p>
<p class="MsoNormal"><span lang="EN-US">INTRODUCTION<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Human behavior recognition and
understanding is the core technology that enables a wide variety of
human-machine systems and applications, e.g., health care, smart homes, and
fitness tracking. Traditional approaches mainly use cameras and wearable
sensors. However, all these approaches have certain disadvantages. For example,
camera based approaches have the limitations of requiring line of sight with
enough lighting and breaching human privacy potentially. Wearable sensor based
approaches are inconvenient sometimes as users usually need to wear certain
sensor-rich devices. Recently, device-free human behavior recognition
approaches (e.g., Wi-Fi based and acoustic based) are attracting increasing
attentions. For instance, compared with traditional approaches, Wi-Fi based
approaches have a set of advantages, e.g., they do not require lighting,
provide better coverage as they can operate through walls, preserve user
privacy, and do not require users to carry any devices as they rely on the
Wi-Fi signals reflected by humans. As a result, the recognition of quite a
number of behaviors that are difficult based on traditional approaches have now
become possible, e.g., fine-grained movements (e.g., gesture and lip language),
keystrokes, drawings, gait patterns, vital signals (e.g., breathing rate and
heart rate), etc. However, device-free behavior recognition still faces a
number of challenges: How to build device-free behavior recognition models and
algorithms that are robust for different humans? How to overcome the impact of
noise and ensure the performance of device-free systems? How to simultaneously
recognize the behavior of multiple users? How the device-free system can adapt
and evolve according to the environment change?<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"> </span></p>
<p class="MsoNormal"><span lang="EN-US">This special issue of ACM/Springer Journal
of Personal and Ubiquitous Computing provides the opportunity for researchers
and product developers to review and discuss the state-of-the-art and trends of
device-free behavior recognition techniques and systems. <o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"> </span></p>
<p class="MsoNormal"><span lang="EN-US">In the light of the above, the main purpose
of this special issue is threefold:<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">(1) To promote unprecedented approaches and
techniques in signal processing, feature extraction, data mining and model
construction for device-free human behavior recognition;<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">(2) To identify open issues which remain a
challenge towards the convergence of computation theories and technologies for device-free
behavior recognition;<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">(3) To exploit novel application areas and
demonstrate the benefits of device-free behavior recognition in contrast with
more traditional sensing approaches.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"> </span></p>
<p class="MsoNormal"><span lang="EN-US">Topics may include (but are not limited
to):<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">- Device-free Human Behavior Recognition
Algorithms<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">- Signal Processing Techniques for
Device-free Human Behavior Recognition<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">- Data Mining Techniques for Device-free
Human Behavior Recognition<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">- New Device-free Sensing Modes for Human
Behavior Recognition<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">- Novel Human Behavior Recognition
Applications/Systems based on Device-free Sensing<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">- Evaluation Metrics and Empirical Studies
of Device-free Human Behavior Recognition<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">- Deployment Experiences for Device-free
Human Behavior Recognition<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"> </span></p>
<p class="MsoNormal"><span lang="EN-US">Submissions<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Papers must be tailored to the problems of device-free
behavior recognition and explicitly consider the above issues. The Guest
Editors reserve the right to reject papers they deem to be out of scope of this
SI. Only originally unpublished contributions and invited articles will be
considered for this SI.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"> </span></p>
<p class="MsoNormal"><span lang="EN-US">Guest Editors<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Bin Guo, guob@nwpu.edu.cn, Northwestern
Polytechnical University (China)<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Yanyong Zhang, yyzhang@winlab.rutgers.edu, Rutgers
University (USA)<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Daqing Zhang, dqzhang@sei.pku.edu.cn, Peking
University (China) / Institute Mines-Telecom (France)<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Zhu Wang, wangzhu@nwpu.edu.cn, Northwestern
Polytechnical University (China)<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"> </span></p>
<p class="MsoNormal"><span lang="EN-US">Important Dates<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Manuscript Submission: May 1, 2018<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Decision Notification: August 1, 2018<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Final Manuscript Due Date: August 15, 2018<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Publication Date (tentative): October, 2018<o:p></o:p></span></p></div>