2nd Call-for-Papers: SI on Looking At People: Analyzing Human Behavior from Social Media Data @ International Journal of Computer Vision

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Hugo Jair

Jan 7, 2019, 9:13:52 PM1/7/19
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[Apologies for multiple postings]

Special Issue on "Looking At People: Analyzing Human Behavior from
Social Media Data"
International Journal of Computer Vision

Although great advances have been obtained in the "Looking at People"
field, it is only recently that attention has focused on problems
connected to more complex and subconscious behavior. For instance,
personality and social behavior are only starting to be explored from
the computer vision and multimedia information processing
perspectives. This is often due to a lack of data and benchmarks to
evaluate these type of tasks.

Nevertheless, the availability of massive amounts of multimodal
information together with the dominance of social networks as a
fundamental channel where users interact, have attracted the interest
of the community in this direction of research. Tools for effectively
analyzing these sort of behaviors have a major impact into everyone's
life, with applications in health (e.g., support for mental
disorders), security (e.g., forensics, preventive applications), human
computer/machine/robot interaction (e.g., affective/interactive
interfaces) and even entertainment (e.g., user-tailored systems).

This special issue focuses in all aspects of computer vision and
pattern recognition devoted to the automatic analysis of human
behavior in social media from visual and multimodal information. The
focus is on the analysis of human behavior that is not visually
obvious, i.e., unconscious behavior and situations in which the sole
visual analysis is insufficient to provide a satisfactory solution.
Submissions in other aspects of looking at people may be considered as

Prospective articles should make fundamental or practical
contributions to the field. Topics of interest include (but are not
limited to):
- Human behavior analysis from visual and multimodal information, with
emphasis on unconscious behaviors, including, but not limited to:
personality analysis, deception detection, social behavior analysis
- All aspects of human behavior analysis in the context of social
networks using multimodal information, including, but not limited to:
gesture/action, emotion recognition, personality analysis and
human-computer interaction
- Personality analysis and deception detection from multimodal
information, including textual, visual, and audible information
- Information retrieval, categorization and clustering of social
networks data, including images, text, and videos for the analysis of
human behavior
- Analysis of human intention from social networks data involving
multimodal information
- New tasks, data sets and benchmarks on human behavior analysis from
multimodal information
- Multimodal machine learning, deep learning, active learning, and
transfer learning for human behavior analysis in social media
- Multimodal zero-shot learning, and unsupervised learning for the
analysis of unconscious human behaviors
- Crowdsourcing, community contributions, and social multimedia
- Information fusion for the analysis of human behavior in the context
of social networks
- Large-scale and web-scale multimodal analysis of social media
- Explainability and fairness in multimodal AI systems for human
behavior analysis
- Applications of unconscious behavior analysis methods, e.g.,
medicine, sports, commerce, lifelogs, travel, security, environment.

*** Submission guidelines ***
All the papers should be full journal length submissions and follow
the guidelines set out by International Journal of Computer Vision:

Manuscripts should be submitted online at:
choosing "S.I. : Analyzing Human Behavior from Social Media Data" as
article type.

When uploading your paper, please ensure that your manuscript is
marked as being for this special issue. Information about the
manuscript (title, full list of authors, corresponding author's
contact, abstract, and keywords) should be also sent to the
corresponding editors (see information below).

Submitted papers should present original, unpublished work, relevant
to at least one of the topics of the special issue. All submitted
papers will be evaluated on the basis of relevance, significance of
contribution, technical quality, scholarship, and quality of
presentation, by at least three independent reviewers. It is the
policy of the journal that no submission, or substantially overlapping
submission, be published or be under review at another journal or
conference at any time during the review process.

*** Important dates ***
Manuscripts Due: 15 March 2019
Publication: 1st quarter of 2020

*** Guest editors ***
Hugo Jair Escalante (hugo...@gmail.com), INAOE, Mexico & ChaLearn, USA
Bogdan Ionescu, University Politehnica of Bucharest, Romania
Esaú Villatoro, UAM-C, Mexico
Gabriela Ramírez, UAM-C, Mexico
Sergio Escalera, Computer Vision Center (UAB) & University of Barcelona, Spain
Martha Larson, Radboud University & Delft University of Technology, Netherlands
Henning Müller, University of Applied Sciences Western Switzerland
(HES-SO), Switzerland
Isabelle Guyon, ChaLearn, Berkeley, California, USA
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