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Anja Exler <[log in to unmask]>
Thu, 12 Dec 2019 14:07:50 +0100
text/plain (122 lines)
==============================================================
                                                CALL FOR PAPERS
         International Conference on Activity and Behavior Computing 
(ABC 2020)

https://abc-research.github.io/
                                Jun. 22nd - 25th, 2020, Kitakyushu, Japan
                                    In conjunction with ICIEV&IVPR2020
==============================================================


Human Activity Recognition has been researched in thousands of papers
so far, with mobile / environmental sensors in ubiquitous / pervasive
domains, and with cameras in vision domains. As well, Human Behavior
Analysis is also explored for long-term health care, rehabilitation,
emotion recognition, human interaction, and so on. However, many
research challenges remain for realistic settings, such as complex and
ambiguous activities / behavior, optimal sensor combinations, (deep)
machine learning, data collection, platform systems, and killer
applications.  In this conference, we comprehend such research domains
as ABC: Activity and Behavior Computing, and provide an open and a
confluent place for discussing various aspects and the future of the
ABC.

CONFERENCE SCOPES
We welcome 4 categories of papers: regular papers, position papers, 
survey papers,
and challenge papers. The submitted papers are peer reviewed by expert 
researchers,
and accepted based on the research quality.
Accepted papers will be included in Springer Books (TBD, IEEE Xplore and 
SCOPUS
indexed). Selected papers will be invited to submit to the Pattern 
Recognition Letters
journal (5-Year Impact Factor: 2.350) and to International Journal on 
Computer Vision
and Signal Processing.

- Mobile sensor-based ABC
- Environmental sensor-based ABC
- Vision-based ABC
- Multimodal ABC
- Physical / semantic analysis of ABC
- Gait analysis
- Sleep analysis
- Emotion recognition / analysis
- ABC with deep learning
- ABC data mining
- Data collection
- ABC systems
- Interactive ABC
- Healthcare applications
- Sports applications
- Business applications
- Tools for industry
- ABC in the wild

CATEGORIES
- Regular papers: full technical contents which describe the accuracy 
and performance
   of ABC Systems, real deployment cases or application of new paradigms 
such as deep
   learning to ABC.
- Position papers: describe the challenges and future directions of ABC 
based on
   problems that arise when systems are deployed in real settings.
- Survey papers: new perspective or new challenges in ABC based on 
literature survey.
   We do not welcome just compilations of existing research, but do if 
it provides new
   research horizons.
- Challenge papers: TBA, we will provide a dataset and accept results 
for activity recognition
    and papers describing the methods and the results.

FORMAT
- Regular papers: 8-20 pages in single column
- Survey papers: 10-20 pages in single column
- Challenge papers: 4-10 pages in single column
- Position papers: 4-10 pages in single column
- Please use Springer Contributed Book format (see website).
- Submit from Microsoft CMT for ICIEV2020 and select ABC (see website).

IMPORTANT DATES
- Paper submission:  Jan. 17th, 2020 (Anywhere on Earth)!
- Review result:         Mar. 13th, 2020
- Camera ready:        Apr. 20th, 2020
- Conference:            Jun., 22nd - 25th, 2020

----
COMMITTEE

GENERAL CHAIRS
Sozo Inoue, Kyushu Institute of Technology / Riken, Japan
Atiqur Rahman Ahad, University of Dhaka, Bangladesh / Osaka University, 
Japan

PROGRAM CHAIRS
Daniel Roggen, University of Sussex, UK
Kaori Fujinami, Tokyo University of Agriculture and Technology, Japan

ADVISORY BOARD
Paul Lukowicz, DFKI, Germany
Kristof Van Laerhoven, University of Siegen, Germany
Daniel Roggen, University of Sussex, UK
Michael Beigl, Karlsruhe Institute of Technology, Germany
Jeffry Cohn, University of Pittsburgh, USA
Anind Dey, University of Washinton, USA
Nobuo Kawaguchi, Nagoya University, Japan
==============================================================


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