Dear colleagues,
We are inviting participation to biometric competition on "6th *Sclera
Segmentation
Recognition Benchmarking Competition(SSBC 2019)", *in conjunction with the
12th* IAPR **International Conference on Biometrics (ICB 2019)*.
Details about the competition can be found at
https://sites.google.com/view/ssbc2019/home
Please find a call for participation flyer attached with the email. Please
feel free to register for the same.
*We will** welcome the top ranking participant to join as co-author of the
technical report of the competition that will be submitted to ICB 2019**.*
Feel free to contact Abhijit Das if you have any further questions.
Kindly circulate this email to others who might be interested.
We look forward to your contributions!
Best regards
Organizers SSBC 2019
Abhijit Das (Inria, France)
Umpada Pal (ISI, Kolkata, India)
Michael Blumenstein (UTS , Australia)
Dear colleagues,
We are inviting paper submissions for a special session on “Human Health
Monitoring Based on Computer Vision”, as part of the 14th IEEE
International Conference on Automatic Face and Gesture Recognition (FG’19,
http://fg2019.org/), Lille, France, May 14-18, 2019. Details on the special
session can be found in the attached call for paper and at
http://fg2019.org/participate/special-sessions/hhmbcv/.
IMPORTANT DATES:
Full Paper Submission: Dec 14th, 2018
Acceptance Notification: Jan 21st, 2019
Camera-Ready Paper Due: Feb 15th 2019
Feel free to contact Abhijit Das if you have any further questions.
Kindly circulate this email to others who might be interested.
We look forward to your contributions!
François Brémond (INRIA, France)
Antitza Dantcheva (INRIA, France)
Abhijit Das (INRIA, France)
Xilin Chen (CAS, China)
Hu Han (CAS, China)
2nd CALL FOR PARTICIPATION
The One-Minute Gradual-Empathy Prediction (OMG-Empathy) Competition
held in partnership with the IEEE International Conference on Automatic
Face and Gesture Recognition 2019 in Lille, France.
https://www2.informatik.uni-hamburg.de/wtm/omgchallenges/omg_empathy.html
I. Aim and Scope
The ability to perceive, understand and respond to social interactions in a
human-like manner is one of the most desired capabilities in artificial
agents, particularly social robots. These skills are highly complex and
require a focus on several different aspects of research, including
affective understanding. An agent which is able to recognize, understand
and, most importantly, adapt to different human affective behaviors can
increase its own social capabilities by being able to interact and
communicate in a natural way.
Emotional expression perception and categorization are extremely popular in
the affective computing community. However, the inclusion of emotions in
the decision-making process of an agent is not considered in most of the
research in this field. To treat emotion expressions as the final goal,
although necessary, reduces the usability of such solutions in more complex
scenarios. To create a general affective model to be used as a modulator
for learning different cognitive tasks, such as modeling intrinsic
motivation, creativity, dialog processing, grounded learning, and
human-level communication, only emotion perception cannot be the pivotal
focus. The integration of perception with intrinsic concepts of emotional
understanding, such as a dynamic and evolving mood and affective memory, is
required to model the necessary complexity of an interaction and realize
adaptability in an agent's social behavior.
Such models are most necessary for the development of real-world social
systems, which would communicate and interact with humans in a natural way
on a day-to-day basis. This could become the next goal for research on
Human-Robot Interaction (HRI) and could be an essential part of the next
generation of social robots.
For this challenge, we designed, collected and annotated a novel corpus
based on human-human interaction. This novel corpus builds on top of the
experience we gathered while organizing the OMG-Emotion Recognition
Challenge, making use of state-of-the-art frameworks for data collection
and annotation.
The One-Minute Gradual Empathy datasets (OMG-Empathy) contain multi-modal
recordings of different individuals discussing predefined topics. One of
them, the actor, shares a story about themselves while the other, the
listener, reacts to it emotionally. We annotated each interaction based on
the listener's own assessment of how they felt while the interaction was
taking place.
We encourage the participants to propose state-of-the-art solutions not
only based on deep, recurrent and self-organizing neural networks but also
traditional methods for feature representation and data processing. We also
enforce that the use of contextual information, as well as personalized
solutions for empathy assessment, will be extremely important for the
development of competitive solutions.
II. Competition Tracks
We let available for the challenge a pre-defined set of training,
validation and testing samples. We separate our samples based on each
story: 4 stories for training, 1 for validation and 3 for testing. Each
story sample is composed of 10 videos with interactions, one for each
listener. Although using the same training, validation and testing data
split, we propose two tracks which will measure different aspects of
self-assessed empathy:
The Personalized Empathy track, where each team must predict the empathy of
a specific person. We will evaluate the ability of proposed models to learn
the empathic behavior of each of the subjects over a newly perceived story.
We encourage the teams to develop models which take into consideration the
individual behavior of each subject in the training data.
The Generalized Empathy track, where the teams must predict the general
behavior of all the participants over each story. We will measure the
performance of the proposed models to learn a general empathic measure for
each of the stories individually. We encourage the proposed models to take
into consideration the aggregated behavior of all the participants for each
story and to generalize this behavior in a newly perceived story.
The training and validation samples will be given to the participants at
the beginning of the challenge together with all the associated labels. The
test set will be given to the participants without the associated labels.
The team`s predictions on the test set will be used to calculate the final
metrics of the challenge.
III. How to Participate
To participate in the challenge, please send us an email to barros @
informatik.uni-hamburg.de with the title "OMG-Empathy Team Registration".
This e-mail must contain the following information:
Team Name
Team Members
Affiliation
Participating tracks
We split the corpus into three subsets: training, validation, and testing.
The participants will receive the training and validation sets, together
with the associated annotations once they subscribe to the challenge. The
subscription will be done via e-mail. Each participating team must consist
of 1 to 5 participants and must agree to use the data only for scientific
purposes. Each team can choose to take part in one or both the tracks.
After the training period is over, the testing set will be released without
the associated annotations.
Each team must submit, via e-mail, their final predictions as a .csv file
for each video on the test set. Together with the final submission, each
team must send a short 2-4 pages paper describing their solution published
on Arxiv and the link for a GitHub page to their solution. If a team fails
to submit any of these items, their submission will be invalidated. Each
team can submit 3 complete submissions for each track.
IV. Important Dates
25th of September 2018 - Opening of the Challenge - Team registrations begin
1st of October 2018 - Training/validation data and annotation available
3rd of December 2018 - Test data release
5th of December 2018 - Final submission (Results and code)
7th of December 2018 - Final submission (Paper)
10th of December 2018 - Announcement of the winners
V. Organization
Pablo Barros, University of Hamburg, Germany
Nikhil Churamani, University of Cambridge, United Kingdom
Angelica Lim, Simon Fraser University, Canada
Stefan Wermter, Hamburg University, Germany
--
Dr. Pablo Barros
Postdoctoral Research Associate - Crossmodal Learning Project (CML)
Knowledge Technology
Department of Informatics
University of Hamburg
Vogt-Koelln-Str. 30
22527 Hamburg, Germany
Phone: +49 40 42883 2535
Fax: +49 40 42883 2515
barros at informatik.uni-hamburg.dehttp://www.pablobarros.nethttps://www.inf.uni-hamburg.de/en/inst/ab/wtm/people/barros.htmlhttps://www.inf.uni-hamburg.de/en/inst/ab/wtm/
Nanyang Technological University (NTU) in Singapore has open calls for several postdoctoral fellowships, which are also open for research on vision and perception. There are currently three labs in the area of vision research:
- Charles OR (charlesor(a)ntu.edu.sg<mailto:charlesor@ntu.edu.sg>)
Face perception, motion perception, form perception, EEG, eye movements, computational modelling, psychophysics;
http://research.ntu.edu.sg/expertise/academicprofile/Pages/StaffProfile.asp…
- Gerrit MAUS (maus(a)ntu.edu.sg<mailto:maus@ntu.edu.sg>)
Eye movements, eye blinks, filling-in, interpolation and extrapolation in vision, prediction, motion perception; psychophysics, fMRI, TMS;
http://blogs.ntu.edu.sg/perception
- Hong XU (xuhong(a)ntu.edu.sg<mailto:xuhong@ntu.edu.sg>)
Heading/Self-motion perception in navigation, face and object perception, attention and eye movements, virtual reality, EEG, electrophysiology, modelling, psychophysics;
http://www.ntu.edu.sg/home/xuhong/
We have access to state-of-the-art facilities for psychophysics, virtual reality, eye tracking, EEG, MEG, fMRI, fNIRS, TMS, and tDCS.
Feel free to contact any of us for more information or to discuss potential proposals.
The fellowship ad below (Deadline: 30 November) is currently offered by the College of Humanities, Arts, and Social Sciences, NTU.
There are two more opportunities available at NTU:
- for research related to Artificial Intelligence (Walllenberg - NTU Presidential Postdoctoral Fellowship, http://www.ntu.edu.sg/ppf/Pages/home.aspx),
- for research in any area by PhD graduates from Swedish Universities (Wallenberg - NTU Postdoctoral Fellowship, call open from Dec 1st, https://kaw.wallenberg.org/utlysningar/wallenberg-foundation-postdoctoral-f…)
Best Regards,
Charles OR, Gerrit MAUS, Hong XU
Assistant Professors (Psychology)
School of Social Sciences
College of Humanities, Arts, and Social Sciences
Nanyang Technological University, Singapore
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The College of Humanities, Arts, and Social Sciences, Nanyang Technological University (NTU) invites applications from eligible candidates to join us as Postdoctoral Fellows for the Academic Year 2019.
The Postdoctoral Fellowships are for one year, renewable for a second year, subject to satisfactory performance. Applicants are strongly advised to explore the research interests of the College’s faculty members to identify potential faculty mentors.
Applicants must possess a doctoral degree issued no more than 3 years prior to the time of application (i.e. the degree must have been obtained after Jan 1, 2016). Candidates who are finishing up their degrees must have their doctoral degrees conferred by July 2019.
Owing to the interdisciplinary nature of the fellowship, applicants are expected to propose a research project to demonstrate how their expertise crosses different disciplines and relates to the specific Research Theme they are applying for.
Details are available at:
http://class.cohass.ntu.edu.sg/Research/Pages/Postdoctoral-Fellowship-2019.…
Applications and Reference Letters must reach the College by 30 November, 2018 (11:59pm Singapore Time UTC+8). Successful candidates are expected to commence their Fellowships in July or August 2019.
Owing to the tight deadline, interested candidates are invited to contact potential faculty mentors as soon as possible, with curriculum vitae and a brief research statement provided.
Application and enquiries should be addressed to:
The Associate Dean (Research)
College of Humanities, Arts, and Social Sciences
Email: AD-HASS-RESEARCH(a)ntu.edu.sg<mailto:AD-HASS-RESEARCH@ntu.edu.sg>
NTU is a young and research-intensive university ranking consistently amongst the top 10 in Asia and the 1st amongst young universities under 50. It has been ranked consistently and progressively under the top 100 universities in the world by the Times Higher Education since 2013, with its latest ranking at 51. Singapore is a fascinating, dynamic multi-cultural city in Southeast Asia with a large expat community, and a great hub for exploring neighbouring travel destinations.
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