Last CFPs - Deadline Extended to May 15 - SI on Looking At People: Analyzing Human Behavior from Social Media Data @ International Journal of Computer Vision

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Hugo Jair

Mar 21, 2019, 12:55:14 PM3/21/19
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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: May, 15 2019 (Final Extension)

*** Guest editors ***

Hugo Jair Escalante (, 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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