Improving classification accuracy of youtube videos by exploiting focal points in social tags

Amogh Mahapatra, Komal Kapoor, Ravindra Kasturi, Jaideep Srivastava

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Past literature [1] has shown that problems involving tacit communication among humans and agents are better solved by identifying communication 'focal' points based on domain specific human biases. Cast differently, classification of user-generated content into generalized categories is the equivalent of automated programs trying to match human adjudged labels. It seems logical to suspect that identification and incorporation of features generally found salient by humans or 'focal points', can allow an automated agent to better match human adjudged labels in classification tasks. In this paper, we leverage this correspondence, by using domain-specific focal points to further inform the classification algorithms of the inherent human biases. We empirically evaluate our method, by classifying YouTube videos using user-annotated tags. Improvements in classification accuracy over the state-of-the-art classification techniques on using our transformed (using focal points) and highly reduced feature space reveals the value of the approach in subjective classification tasks.

Original languageEnglish
Title of host publicationElectronic Proceedings of the 2013 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2013
DOIs
Publication statusPublished - 29 Nov 2013
Event2013 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2013 - San Jose, CA, United States
Duration: 15 Jul 201319 Jul 2013

Publication series

NameElectronic Proceedings of the 2013 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2013

Conference

Conference2013 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2013
CountryUnited States
CitySan Jose, CA
Period15/7/1319/7/13

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Keywords

  • Classification
  • Focal Points
  • Human Salience

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition

Cite this

Mahapatra, A., Kapoor, K., Kasturi, R., & Srivastava, J. (2013). Improving classification accuracy of youtube videos by exploiting focal points in social tags. In Electronic Proceedings of the 2013 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2013 [6618382] (Electronic Proceedings of the 2013 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2013). https://doi.org/10.1109/ICMEW.2013.6618382