Fwd: [Announcements] [CFP] HASCA@Ubicomp'16: 4th Int Workshop on Human Activity Sensing Corpus and Applications - Towards Open-Ended Context Awareness
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Sozo Inoue
May 11, 2016, 12:09:28 AM5/11/16
to hasc-jp
HASC ML登録のみなさま
国際ワークショップHASCAがUbicomp/ISWC 併設ワークショップとして採択されました。
6月7日が投稿締め切りとなります。
投稿のご検討よろしくお願い致します！
-----
http://sozolab.jp https://www.facebook.com/sozolab/
Sozo INOUE, Assoc. Prof., Kyushu Inst. Tech.
九州工業大学 井上創造
---------- Forwarded message ----------
From: Daniel Roggen <daniel...@ieee.org>
Date: 2016-05-06 17:50 GMT+09:00
Subject: [Announcements] [CFP] HASCA@Ubicomp'16: 4th Int Workshop on
Human Activity Sensing Corpus and Applications - Towards Open-Ended
Context Awareness
To: announ...@ubicomp.org
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
CALL FOR CONTRIBUTIONS
4th Int Workshop on Human Activity Sensing Corpus and Applications (HASCA)
-
Towards Open-Ended Context Awareness
Workshop at Ubicomp/ISWC'16
http://hasca2016.hasc.jp
http://lifelearn-project.org
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
SUMMARY
-------
The objective of this workshop is to share the experiences among current
researchers around the challenges of real-world activity recognition,
the role of datasets and tools, and breakthrough approaches towards open-ended
contextual intelligence.
This workshop deals with the challenges of designing reproducible experimental
setups, running large-scale dataset collection campaigns, designing activity
and context recognition methods that are robust and adaptive, and evaluating
systems in the real world.
As a special topic this year, we wish to reflect on the challenges and
possible approaches to recognise situations, events or activities outside of
a statically pre-defined pool - which is the current state of the art - and
instead adopt an "open-ended view" on activity and context awareness. This
may take combinations of advances in the automatic discovery of relevant
patterns in sensor data, advances in experience sampling and wearable
technologies to unobtrusively discover the semantic meaning of such patterns,
advances in crowd-sourcing of dataset acquisition and annotation and new
"open-ended" human activity modeling techniques.
CALL FOR CONTRIBUTIONS
----------------------
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, such as papers describing the formats, styles or methodologies
for data collection. Cloud-sourcing data collection or 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 corpus, which is
called “Data Centric Research”. Also, we solicit of the experience of
using large-scale human activity sensing corpus. Using large-scape
corpus with 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 and suitable tools for management of sensor data,
activity recognition researchers could be more focused on their research
theme. However, development of tools or algorithms for sharing among the
research community is not much appreciated. In this workshop, we solicit
development reports of tools and algorithms for forwarding the community.
- *Real World Application and Experiences*.
Activity recognition “in the Lab” usually works well. However, it is
not true in the real world. In this workshop, we also solicit the
experiences from real world applications. There is a huge gap/valley
between “Lab Environment” and “Real World Environment”. Large scale human
activity sensing corpus will help to overcome this gap/valley.
- *Sensing Devices and Systems*
Data collection is not only performed by the “off the shelf” sensors.
There is a requirement to develop some special devices to obtain some
sort of information. There is also a research area about the development
or evaluate the system or technologies for data collection.
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 intelligently
querying the user or using novel devices (e.g. smartwatches) are
likely to play an important role to provide user-contributed annotations
of their own activities.
- *Unsupervised pattern discovery**.
Discovering meaningful repeating patterns in sensor data can be
fundamental in informing other elements of the system, such as
inquiring user or triggering annotation crowd sourcing.
- *Dataset acquisition and annotation*, *crowd-sourcing*, *web-mining*.
A wide abundance of sensor data is potentially in reach with users
instrumented with their mobile phones and other wearables.
Capitalising 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*, *lifelong learning*.
The ability to translate recognition models accross 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.
AREAS OF INTEREST
-----------------
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
FORMAT
------
We invite two kinds of submissions:
Full research papers up to 10 pages
Short technical papers up to 5 pages
All publications will be peer reviewed together with their contribution
to the topic of the workshop.
KEY DATES
---------
* Submission: June 7, 2016
* Notification of acceptance: June 21, 2016
* Camera ready: June 28, 2016
_______________________________________________
Announcements mailing list
Announ...@ubicomp.org
http://ubicomp.org/mailman/listinfo/announcements_ubicomp.org
国際ワークショップHASCAがUbicomp/ISWC 併設ワークショップとして採択されました。
6月7日が投稿締め切りとなります。
投稿のご検討よろしくお願い致します！
-----
http://sozolab.jp https://www.facebook.com/sozolab/
Sozo INOUE, Assoc. Prof., Kyushu Inst. Tech.
九州工業大学 井上創造
---------- Forwarded message ----------
From: Daniel Roggen <daniel...@ieee.org>
Date: 2016-05-06 17:50 GMT+09:00
Subject: [Announcements] [CFP] HASCA@Ubicomp'16: 4th Int Workshop on
Human Activity Sensing Corpus and Applications - Towards Open-Ended
Context Awareness
To: announ...@ubicomp.org
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
CALL FOR CONTRIBUTIONS
4th Int Workshop on Human Activity Sensing Corpus and Applications (HASCA)
-
Towards Open-Ended Context Awareness
Workshop at Ubicomp/ISWC'16
http://hasca2016.hasc.jp
http://lifelearn-project.org
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
SUMMARY
-------
The objective of this workshop is to share the experiences among current
researchers around the challenges of real-world activity recognition,
the role of datasets and tools, and breakthrough approaches towards open-ended
contextual intelligence.
This workshop deals with the challenges of designing reproducible experimental
setups, running large-scale dataset collection campaigns, designing activity
and context recognition methods that are robust and adaptive, and evaluating
systems in the real world.
As a special topic this year, we wish to reflect on the challenges and
possible approaches to recognise situations, events or activities outside of
a statically pre-defined pool - which is the current state of the art - and
instead adopt an "open-ended view" on activity and context awareness. This
may take combinations of advances in the automatic discovery of relevant
patterns in sensor data, advances in experience sampling and wearable
technologies to unobtrusively discover the semantic meaning of such patterns,
advances in crowd-sourcing of dataset acquisition and annotation and new
"open-ended" human activity modeling techniques.
CALL FOR CONTRIBUTIONS
----------------------
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, such as papers describing the formats, styles or methodologies
for data collection. Cloud-sourcing data collection or 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 corpus, which is
called “Data Centric Research”. Also, we solicit of the experience of
using large-scale human activity sensing corpus. Using large-scape
corpus with 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 and suitable tools for management of sensor data,
activity recognition researchers could be more focused on their research
theme. However, development of tools or algorithms for sharing among the
research community is not much appreciated. In this workshop, we solicit
development reports of tools and algorithms for forwarding the community.
- *Real World Application and Experiences*.
Activity recognition “in the Lab” usually works well. However, it is
not true in the real world. In this workshop, we also solicit the
experiences from real world applications. There is a huge gap/valley
between “Lab Environment” and “Real World Environment”. Large scale human
activity sensing corpus will help to overcome this gap/valley.
- *Sensing Devices and Systems*
Data collection is not only performed by the “off the shelf” sensors.
There is a requirement to develop some special devices to obtain some
sort of information. There is also a research area about the development
or evaluate the system or technologies for data collection.
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 intelligently
querying the user or using novel devices (e.g. smartwatches) are
likely to play an important role to provide user-contributed annotations
of their own activities.
- *Unsupervised pattern discovery**.
Discovering meaningful repeating patterns in sensor data can be
fundamental in informing other elements of the system, such as
inquiring user or triggering annotation crowd sourcing.
- *Dataset acquisition and annotation*, *crowd-sourcing*, *web-mining*.
A wide abundance of sensor data is potentially in reach with users
instrumented with their mobile phones and other wearables.
Capitalising 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*, *lifelong learning*.
The ability to translate recognition models accross 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.
AREAS OF INTEREST
-----------------
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
FORMAT
------
We invite two kinds of submissions:
Full research papers up to 10 pages
Short technical papers up to 5 pages
All publications will be peer reviewed together with their contribution
to the topic of the workshop.
KEY DATES
---------
* Submission: June 7, 2016
* Notification of acceptance: June 21, 2016
* Camera ready: June 28, 2016
_______________________________________________
Announcements mailing list
Announ...@ubicomp.org
http://ubicomp.org/mailman/listinfo/announcements_ubicomp.org
Sozo Inoue
May 31, 2016, 9:05:52 PM5/31/16
to hasc-jp
HASC ML登録のみなさま
国際ワークショップHASCA@ドイツの締め切りが6月7日となっています。
ふるってのご投稿をお待ちしております!
国際ワークショップHASCA@ドイツの締め切りが6月7日となっています。
ふるってのご投稿をお待ちしております!
Sozo Inoue
Jun 7, 2016, 3:39:50 AM6/7/16
to hasc-jp
HASC ML登録の皆様
HASCA ワークショップの締め切りが，6月19日まで伸びました．
ふるってのご投稿をお願い致します．
by河口先生代理 ．
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
CALL FOR CONTRIBUTIONS
4th Int Workshop on Human Activity Sensing Corpus and Applications (HASCA)
-- Towards Open-Ended Context Awareness --
Workshop at Ubicomp/ISWC'16
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
KEY DATES
---------
* Submission: *Extended* June 19, 2016 (initially June 7, 2016)
* Notification of acceptance: *Extended* June 27, 2016 (initially June 21, 2016)
* Camera ready: *Extended* July 4, 2016 (initially June 28, 2016)
SUMMARY
-------
This workshop deals with the challenge and possible approaches to recognise
human activities and the context in which they occur outside of a statically
pre-defined pool of situations, events or activities of interest.
Some of the avenues to address the current status-quo include
combinations of advances in the automatic discovery of relevant patterns
in sensor data, advances in experience sampling and wearable technologies
to unobtrusively discover the semantic meaning of such patterns, advances
in crowd-sourcing of dataset acquisition and annotation and new
"open-ended" human activity modeling techniques.
CALL FOR CONTRIBUTIONS
----------------------
The objective of this workshop is to gather the community to think how
human activity and context recognition could be approached beyond the
traditional "closed set" approach. We call for any contributions shown
to address aspects related to this fundamental challenge.
We expect the following domains to be relevant contributions to this workshop
(but not limited to):
- *Mobile experience sampling*, *experience sampling strategies*.
Advances in experience sampling approaches, for instance intelligently
querying the user or using novel devices (e.g. smartwatches) are
likely to play an important role to provide user-contributed annotations
of their own activities.
- *Unsupervised pattern discovery**.
Discovering meaningful repeating patterns in sensor data can be
fundamental in informing other elements of the system, such as
inquiring user or triggering annotation crowd sourcing.
- *Dataset acquisition and annotation*, *crowd-sourcing*, *web-mining*.
A wide abundance of sensor data is potentially in reach with users
instrumented with their mobile phones and other wearables.
Capitalising 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*.
The ability to translate recognition models accross 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.
- *Applications*.
Experiences or insights from deployments are welcome, especially
from those applications most likely to benefit from open-ended context
awareness.
FORMAT
------
Contributions are 6 pages maximum in ACM SIGCHI format.
All publications will be peer reviewed and their contribution to
open-ended contextual intelligence will be evaluated.
KEY DATES
---------
* Submission: *Extended* June 19, 2016 (initially June 7, 2016)
* Notification of acceptance: *Extended* June 27, 2016 (initially June 21, 2016)
* Camera ready: *Extended* July 4, 2016 (initially June 28, 2016)
2016年5月11日水曜日、Sozo Inoue<so...@mns.kyutech.ac.jp>さんは書きました:
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