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Tsuyoshi Okita <[log in to unmask]>
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Tsuyoshi Okita <[log in to unmask]>
Sat, 28 Jul 2018 14:05:32 +0900
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Sorry for the multiple posting.

We have several requests for the deadline extension!! Now it is Aug 2!!

-------------------------------------CFP starts------------------------

*6th Int Workshop on Human Activity Sensing Corpus and Applications (HASCA)*
in conjunction with* ACM Ubicomp/ISWC 2018*
Singapore, Singapore

* Submission Deadline: Aug 2, 2018 (extended) *
* Workshop Date: October 12, 2018 *


The objective of this workshop is to share the experiences among
researchers about current challenges of real-world activity
recognition with newly developed datasets and tools, breaking through
towards open-ended contextual intelligence.

This workshop discusses the challenges of designing reproducible
experimental setups, the large-scale dataset collection campaigns, the
activity and context recognition methods that are robust and adaptive,
and evaluation systems in the real world.

As a special topic of this year we will reflect on the challenges to
recognize situations, events and/or activities among the statically
predefined pools and beyond - which is the current state of the art -
and instead we will adopt an "open-ended view" on activity and context
awareness. This may result in combinations of the automatic discovery
of relevant patterns in sensor data, the experience sampling and
wearable technologies to unobtrusively discover the semantic meaning
of such patterns, the crowd-sourcing of dataset acquisition and
annotation, and new "open-ended" human activity modeling techniques.


We expect the following domains to be relevant contributions to this
workshop (but not limited to):

- **Data collection*, *Corpus construction*. *
Experiences or reports from data collection and/or corpus construction
projects, including papers which describes the formats, styles and/or
methodologies for data collection. Cloud-sourcing data collection and
participatory sensing also could be included in this topic.

- **Effectiveness of Data*, *Data Centric Research*. *
There is a field of research based on the collected corpora, which is so
called "data centric research". Also, we call for the experience of using
large-scale human activity sensing corpora. Using large-scale corpora with
an analysis by machine learning, there will be a large space for improving
the performance of recognition results.

- **Tools and Algorithms for Activity Recognition*.*
If we have appropriate tools for the management of sensor data,
activity recognition researchers could have more focused on their actual
research theme. This is because the developed tools and algorithms are
often not shared among the research community. In this workshop, we solicit
reports on developed tools and algorithms for forwarding to the community.

- **Real World Application and Experiences*. *
Activity recognition "in the lab" usually works well. However, it does not
scale well with real world data. In this workshop, we also solicit the
experiences from real world applications. There is a huge gap between "lab"
and "real world” environments . Large-scale human activity sensing corpora
will help to overcome this gap.

- **Sensing Devices and Systems* *
Data collection is not only performed by the "off-the-shelf" sensors but
also the newly developed sensors which supply information which has not
been investigated. There is also a research area about the development of
new platform for data collection or the evaluation tools for collected data.

In light of this year's special emphasis on open-ended contextual
awareness, we wish cover these topics as well:

- **Mobile Experience Sampling*, *Experience Sampling Strategies*.*
Advances in experience sampling approaches, for instance intelligent user
query or those using novel devices (e.g. smartwatches), are likely to play
an important role to provide user-contributed annotations of their own

- **Unsupervised Pattern Discovery*. *
Discovering meaningful patterns in sensor data in an unsupervised manner
can be needed in the context of informing other elements of the system by
inquiring the user and by triggering the annotation with crowd-sourcing.

- **Dataset Acquisition and Annotation*, *Crowd-Sourcing*, *Web-Mining*.*
A wide abundance of sensor data is potentially within the reach of users
instrumented with their mobile phones and other
wearables. Capitalizing on crowd-sourcing to create larger datasets in a
cost effective manner may be critical to open-ended activity recognition.
Many online datasets are also available and could be used to bootstrap
recognition models.

- **Transfer Learning*, *Semi-Supervised Learning*, *Lifelog Learning*. *
The ability to translate recognition models across modalities or to
use minimal forms of supervision would allow to reuse datasets in a wider
range of domains and reduce the costs of acquiring annotations.


   - Human Activity Sensing Corpus
   - Large Scale Data Collection
   - Data Validation
   - Data Tagging / Labeling
   - Efficient Data Collection
   - Data Mining from Corpus
   - Automatic Segmentation
   - Performance Evaluation
   - Man-machine Interaction
   - Noise Robustness
   - Non Supervised Machine Learning
   - Sensor Data Fusion
   - Tools for Human Activity Corpus/Sensing
   - Participatory Sensing
   - Feature Extraction and Selection
   - Context Awareness
   - Pedestrian Navigation
   - Social Activities Analysis/Detection
   - Compressive Sensing
   - Sensing Devices
   - Lifelog Systems
   - Route Recognition/Detection
   - Wearable Application
   - Gait Analysis
   - Health-care Monitoring/Recommendation
   - Daily-life Worker Support


The Sussex-Huawei Locomotion Dataset will be used in an activity
recognition challenge with results to be presented at HASCA 2018. To be
part of the final ranking, participants will be required to submit a
detailed paper to the HASCA workshop. The paper should contain technical
description of the processing pipeline, the algorithms and the results
achieved during the development/training phase. The paper submission date
will be set during the competition. The submissions

must follow the HASCA format (up to 10 pages).


We invite three kinds of submissions:

   - Full research papers up to 10 pages
   - Short technical papers up to 5 pages
   - SHL challenge papers up to 10 pages

All publications will be peer reviewed together with their
contribution to the topic of the workshop. Submission is electronic,
using precision submission system. The submission site is open at (select SIGCHI/UbiComp
2018/UbiComp 2018 Workshop - HASCA and push Go button).

All the papers must be formatted as “ACM SIGCHI Extended Abstracts
format” (landscape).  Submissions do not need to be anonymous.

The accepted papers will be published in the UbiComp 2018 adjunct
proceedings, which will be included in the ACM Digital Library.

Full research/short technical papers:

   - Submission deadline : Aug 2, 2018 (extended)
   - Notification of acceptance: Aug 10, 2018
   - Camera ready deadline : Aug 18, 2018
   - Workshop date: October 12, 2018

SHL challenge papers (only the challenge participants):

   - Submission deadline : July 31, 2018

(Check how to register at
ivity-recognition-challenge/ no later than June 20, 2018)



Kazuya MURAO (Ritsumeikan University, Japnan)

Yu ENOKIBORI (Nagoya University, Japan)

Hristijan GJORESKI (Ss. Cyril and Methodius University, Macedonia)

Paula LAGO (Kyushu Institute Technology, Japan)

Tsuyoshi OKITA (Kyushu Institute Technology, Japan)

Pekka SIIRTOLA (University of Oulu, Finland)

Kei HIROI (Nagoya University, Japan)
Philipp M. SCHOLL (University of Freiburg, Germany)


Nobuo Kawaguchi (Nagoya University, Japan)

Nobuhiko Nishio (Ritsumeikan University, Japan)

Daniel Roggen (University of Sussex, UK)

Sozo Inoue (Kyushu Institute of Technology, Japan)

Susanna Pirttikangas (University of Oulu, Finland)

Kristof van Laerhoven (University of Freiburg, Germany)


*------------ *

(+)Hao-Hua Chu, National Taiwan University(Taiwan)
Yu Enokibori, Nagoya University(Japan)
Anja Exler, Karlsruhe Institute of Technology (Germany)
Elisabetta Farella, Fondazione Bruno Kessler (Italy)
Kaori Fujinami, Tokyo University of Agriculture and Technology (Japan)
Kei Hiroi, Nagoya University (Japan)
Gjoreski Hristijan, Sussex University (UK)
Sozo Inoue, Kyushu Institute of Technology (Japan)
Katsuhiko Kaji, Nagoya University (Japan)
Nobuo Kawaguchi, Nagoya University (Japan)
Yoshihiro Kawahara, The University of Tokyo (Japan)
Paula Lago, Kyushu Institute of Technology (Japan)
Philipp M. Scholl, University of Freiburg (Germany)
Shigeyuki Miyagi, University of Shiga Prefecture (Japan)
Kazuya Murao, Kobe University (Japan)
Nobuhiko Nishio, Ritsumeikan University (Japan)
Ren Ohmura, Toyohashi University of Technology (Japan)
Tsuyoshi Okita, Kyushu Institute of Technology (Japan)
Susanna Pirttikangas, University of Oulu (Finland)
Daniel Roggen, University of Sussex (UK)
Masaki Shuzo, Kanagawa University (Japan)
Stephan Sigg, Aalto University (Finland)
Pekka Siirtola, University of Oulu (Finland)
(+)Yasuyuki Sumi, Future University Hakodate (Japan)
Tsutomu Terada, Kobe University (Japan)
Kristof Van Laerhoven, University of Siegen Siegen (Germany)

(+)need to confirm

*If you have any questions please contact *[log in to unmask]

-------------------------------------CFP ends--------------------------

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