Apologies for cross-posting
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FGAHI 2019: CALL FOR PAPERS
2nd International Workshop on Face and Gesture Analysis for Health Informatics
Accepted papers will be published at the CVF open access archive.
Submission Deadline Extended: May 1st, 2019.
The camera-ready deadline: May 15th, 2019.
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The 2d International Workshop on Face and Gesture Analysis for Health Informatics (FGAHI
2019) will be held in conjunction with IEEE CVPR 2019 on June 16th - June 21st, Long Beach, CA.
For details concerning the workshop program, paper submission, and
guidelines please visit our workshop website at:
http://fgahi2019.isir.upmc.fr/
Best regards,
Zakia Hammal
Zakia Hammal, PhD
The Robotics Institute, Carnegie Mellon University
http://www.ri.cmu.edu/http://ri.cmu.edu/personal-pages/ZakiaHammal/
Call For Papers - Frontiers Research Topic: Affective Shared Perception
I. Aim and Scope
Our perception of the world depends on both sensory inputs and prior knowledge. This applies in general to sensing and has particular implications for affective understanding. Humans adapt their social and affective perception as a function of the current stimulation, of the context, of the history of the interaction, and as of the status of the partner. This influences their behavior, which in turn modifies the social and affective perception of both partners and the evolution of the interaction.
Understanding shared perception as part of affective processing will allow us to tackle this problem and to provide the next step towards a real-world affective computing system. The goal of this research topic is to present and discuss new findings, theories, systems, and trends in affective shared perception and computational models.
We are interested in collecting interesting and exciting research from researchers on the areas of social cognition, affective computing, and human-robot interaction, including also, but not restricted to specialists in computer and cognitive science, psychologists, neuroscientists, and specialists in bio-inspired solutions. We envision that it will allow us to tackle the existing problems in this area and it will provide the next step towards a real-world affective computing system.
II. Potential Topics
Topics include, but are not limited to:
- Affective perception and learning
- Affective modulation and decision making
- Developmental perspectives of shared perception
- Machine learning for shared perception
- Bio-inspired approaches for affective shared perception
- Affective processing for embodied and cognitive robots
- Multisensory modeling for conflict resolution in shared perception
- New psychological findings on shared perception
- Assistive aspects and applications of shared affective perception
III. Submission
- Abstract - 24 October 2020
- Paper Submission - 21 February 2021
IV. Guest Editors
Pablo Vinicius Alves De Barros, Italian Institute of Technology (IIT), Genova, Italy
Alessandra Sciutti, Italian Institute of Technology (IIT), Genova, Italy
Ginevra Castellano, Uppsala University, Uppsala, Sweden
Yukie Nagai, The University of Tokyo, Bunkyō, Japan
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Dr. Pablo Barros
Postdoctoral Researcher - CONTACT Unit
Istituto Italiano di Tecnologia – Center for Human Technologies
Via Enrico Melen 83, Building B 16152 Genova, Italy
email: pablo.alvesdebarros(a)iit.it
website: https://www.pablobarros.net<http://www.pablobarros.net><https://www.p>
twitter: @PBarros_br
Dear fellow face researchers,
For a project on cross-cultural differences in eyewitness testimony and
identification, my PhD student Gabi de Bruïne and I are looking for
databases of young adult male faces (real, not generated) from amongst
which to select fillers for photo lineups for a black Gambian target and a
white Dutch target. Ideally, we would like to select Gambian fillers and
Dutch fillers, respectively, but I can imagine that would be hard to find.
An alternative option would be to select a range of sub-Saharan African
fillers and a range of Western European fillers, respectively. Does any of
you perhaps know of any databases we could use?
We have already looked at the face databases collected in this Google
document
<https://docs.google.com/spreadsheets/d/1K-Gelc-HBgbwsDKWraCubGVf30uOrnTo3FT…>,
and found some Western European faces (some Dutch, Scottish, Danish) and
some sub-Saharan African faces (South African), but not enough of a range
to make the lineup work, particularly for the African target. Any help or
advice would be much appreciated!
Many thanks,
Annelies
*Dr. Annelies Vredeveldt*
Associate Professor *| *Department of Criminal Law and Criminology *| *Faculty
of Law *| *VU University Amsterdam
+31 20 59 83 153 *| *a.vredeveldt(a)vu.nl *| *www.annelies.vredeveldt.com
<http://annelies.vredeveldt.com/> *|* www.allp.nl
Dear all
There is a face resource that you may find useful in face-perception research. The faces are computer-generated but are photo-realistic. The link to the company is (Generated Photos):
https://generated.photos/
All the images they offer are free with a link for non-commercial purposes.
For the academic community, they have also made a 10K dataset with meta-data freely available for research:
https://generated.photos/datasets
(scroll towards the bottom)
They have a very good support team, who are very responsive to questions.
Thanks,
Quoc.
===========================
Newcastle University
Biosciences Institute & School of Psychology
Dear all,
for a research project, I am looking for databases that include at least
one measure of facial appearance (i.e., face photographs or rating data)
and at least one measure for the current or previous residence of the
person depicted (i.e., city name, city size, GPS data, zip code, level
of urbanization, or greenness of neighbourhood). Do you know of any
database that has data for both variables (facial apearance /and
/residence) available?
I am grateful for all kind of suggestions. Thank you!
Best wishes,
Claudia Menzel
--
Dr. Claudia Menzel
Social, Environmental, & Economic Psychology
University of Koblenz-Landau
Room H-316, Fortstraße 7, 76829 Landau, Germany
(note that I'm in homeoffice now!)
Homepage: www.uni-koblenz-landau.de/de/landau/fb8/psychaus/AGUmwelt/Personen/menzel
Twitter: @LEPsyUnit
Scientist4Future: https://scientists4future-landau.de
Hi,
I'm looking for a set of non-white male faces (black, Asian or East Asian) with each person displaying the traditional six expressions (happiness, anger, fear, disgust, surprise, sadness and a neutral expression). Does anyone have a set that I could use? If so, please contact me. Thanks!
Graham Hole,
University of Sussex.
Email: grahamh(a)sussex.ac.uk
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CALL FOR PAPERS - HBU 2021
11th International Workshop on Human Behavior Understanding (HBU)
Focus theme: Multi-source aspects of behavioral understanding
Held in conjunction with WACV 2021https://lmi.fe.uni-lj.si/hbu2021
Paper submission deadline: November 5th, 2020
Notifications: November 18th, 2020
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ORGANIZERS
Abhijit Das, Indian Statistical Institute, Kolkata, India
Qiang Ji, Rensselaer Polytechnic Institute, United States
Umapada Pal, Indian Statistical Institute, Kolkata, India
Albert Ali Salah, Utrecht University, The Netherlands
Vitomir Štruc, University of Ljubljana, Slovenia
ABOUT
Domains for human behaviour understanding predominantly (e.g.,
multimedia, human-computer interaction, robotics, affective computing
and social signal processing) rely on advanced pattern recognition
techniques to automatically interpret complex behavioural patterns
generated when humans interact with machines or with other agents. This
is a challenging research area where many issues are still open,
including the joint modelling of behavioural cues taking place at
different time scales, the inherent uncertainty of machine detectable
evidence of human behaviour, the mutual influence of people involved in
interactions, the presence of long term dependencies in observations
extracted from human behaviour, and the important role of dynamics in
human behaviour understanding. Computer vision is a key technology for
analysis and synthesis of human behaviour but stands to gain much from
multi-modality and multi-source processing, in terms of improving
accuracy, resource use, robustness, and contextualization.
This workshop, organized as part of WACV 2021, will gather researchers
dealing with the problem of modelling human behaviour under its multiple
facets (expression of emotions, display of relational attitudes, the
performance of an individual or joint actions, etc.), with particular
attention to multi-source aspects, including multi-sensor,
multi-participant and multi-modal settings. Example challenges are the
additional resource and robustness constraints, explorations in
information fusion, social and contextual aspects of interactions, and
building multi-source representations of social and affective signals
with the goal of advancing the state-of-the-art.
The HBU workshops, previously organized as satellite events to major
conferences in different disciplines such as ICPR’10, AMI’11, IROS’12,
ACMMM’13, ECCV’14, UBICOMP’15, ACMMM’16, FG’18, ECCV’18, ICCV’19 have a
unique aspect of fostering cross-pollination of disciplines, bringing
together researchers from a variety of fields, such as computer vision,
HCI, artificial intelligence, pattern recognition, interaction design,
ambient intelligence, psychology and robotics. The diversity of human
behaviour, the richness of multimodal data that arises from its
analysis, and the multitude of applications that demand rapid progress
in this area ensure that the HBU Workshops provide a timely and relevant
discussion and dissemination platform. For HBU@WACV, we particularly
solicit contributions on human behaviour understanding that combine
multiple sources of information, be it across modalities, sensors, or
subjects under observation. The workshop solicits papers on general
topics related to human behaviour understanding, but with a distinct
focus on multi-source solutions.
TOPICS OF INTEREST
Topics of interest include, but are not limited to:
+ Multimodal solutions for human behaviour modelling and analysis
+ Multimodal solutions towards behavioural biometrics (gait,
handwriting, keystroke dynamics, etc.)
+ Methods for multi-instance learning in behavioural understanding,
+ Analysis of multi-participant settings and of social interactions,
+ Multi-instance representation for characterizing human health,
empathy,
+ Deep learning for multi-party interactions
+ Multimodal deep learning for behaviour understanding
+ Adversarial learning approaches
+ Related sensor technologies
+ Information fusions approach for behaviour analysis
+ Realistic behaviour synthesis in multiple modalities and for
multi-party settings
+ Mobile and wearable systems for behaviour monitoring
+ Datasets and benchmarks
+ Related applications
PAPER SUBMISSION
Submission instruction can be found
athttps://lmi.fe.uni-lj.si/hbu2021/paper-submission/
Please feel free to contact for any further details.
Abhijit Das, Qiang Ji, Umapada Pal, Albert Ali Salah, Vitomir Štruc
HBU 2021 Organizers