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Towards an Affective Video Recommendation System

  • Yancarlos Diaz
  • , Cecilia O. Alm
  • , Ifeoma Nwogu
  • , Reynold Bailey
  • Rochester Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

Video streaming services are prominent in people's lives and there is a need for improved video recommendation systems that adapt to their users in a personalized way. This project uses affective computing and non-invasive sensing to address this issue. Our objective is to develop an approach that uses the viewer's emotional reactions as the basis for recommending new content. To achieve this goal, we must first understand how viewers react to videos. We conducted a study where subjects' facial expressions and skin-estimated pulse were monitored while watching videos. Results showed that our approach can estimate dominant emotions 70% of the time. We found no correlation between the number of emotional reactions people have and how they rate the videos they watch. The pulse estimation is reliable to measure important changes in pulse, however it can still be improved.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages137-142
Number of pages6
ISBN (Electronic)9781538632277
DOIs
StatePublished - Oct 2 2018
Event16th IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018 - Athens, Greece
Duration: Mar 19 2018Mar 23 2018

Publication series

Name2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018

Conference

Conference16th IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018
Country/TerritoryGreece
CityAthens
Period03/19/1803/23/18

Keywords

  • Affective computing
  • photoplethysmography
  • video recommendation

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