Human Behavior Analysis with a Social Signal Processing Perspective

Human Behavior Analysis with a Social Signal Processing Perspective

Lecturer

Cigdem Beyan, cigdem.beyan@unitn.it

Organizer/s

Department of Information Engineering and Computer Science, University of Trento, Italy

Content and organization

Social Signal Processing (SSP) is a cross-disciplinary field that covers studying social signals that 1) are produced during human-human interaction, 2) play a part in the formation and adjustment of relationships between agents (being humans and embodied interfaces) or provide information about the interlocutors, and 3) can be synthetized in embodied interfaces. They can be related to social (inter)actions, social emotions, social evaluations, social attitudes and social relations. The significant part of SSP deals with automatic detection of social attitudes and relations, such as leadership or hostile attitude from the data captured with a wide array of sensors. During this lecture, I will present several datasets and applications (in small groups, mingling scenarios, egocentric vision based) using multimodal data (audio, video, text) and the state-of-the-art machine/deep learning methods.

Course Duration

4 hours

Course Type

Short Course

Participation terms

Both AIDA and non-AIDA students are encouraged to participate in this short course.

If you are an AIDA Student* already, please:
Step (a): Register in the course by following the instructions given in "Teaching" tab of cbeyan.github.io or alternatively by sending an email to cigdem.beyan[at]unitn.it for your registration.

AND
Step (b): Enroll in the same course in the AIDA system using the button below, so that this course enters your AIDA Certificate of Course Attendance.

If you are not an AIDA Student do only step (a).

*AIDA Students should have been registered in the AIDA system already (they are PhD students or PostDocs that belong only to the AIDA Members listed in this page: Members)

Schedule

23-24 February 2022 13.30- 15.30 CET

Language

English

Modality (online/in person):

Online

Notes

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