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Sharing Video Emotional Information in the Web

Sharing Video Emotional Information in the Web

Eva Oliveira (Digital Games Research Centre (DIGARC), Polytechnic Institute of Cávado and Ave, Barcelos, Portugal), Teresa Chambel (LaSIGE, University of Lisbon FCUL, Lisbon, Portugal) and Nuno Magalhães Ribeiro (Centro de Estudos e Recursos Multimediáticos (CEREM), Universidade Fernando Pessoa, Porto, Portugal)
Copyright: © 2013 |Volume: 5 |Issue: 3 |Article: 2 |Pages: 21
ISSN: 1938-0194|EISSN: 1938-0208|EISBN13: 9781466633247|DOI: 10.4018/ijwp.2013070102
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MLA

Oliveira, Eva, Teresa Chambel and Nuno Magalhães Ribeiro. "Sharing Video Emotional Information in the Web." IJWP 5.3 (2013): 19-39. Web. 27 Mar. 2020. doi:10.4018/ijwp.2013070102

APA

Oliveira, E., Chambel, T., & Ribeiro, N. M. (2013). Sharing Video Emotional Information in the Web. International Journal of Web Portals (IJWP), 5(3), 19-39. doi:10.4018/ijwp.2013070102

Chicago

Oliveira, Eva, Teresa Chambel and Nuno Magalhães Ribeiro. "Sharing Video Emotional Information in the Web," International Journal of Web Portals (IJWP) 5 (2013): 3, accessed (March 27, 2020), doi:10.4018/ijwp.2013070102

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Abstract

Video growth over the Internet changed the way users search, browse and view video content. Watching movies over the Internet is increasing and becoming a pastime. The possibility of streaming Internet content to TV, advances in video compression techniques and video streaming have turned this recent modality of watching movies easy and doable. Web portals as a worldwide mean of multimedia data access need to have their contents properly classified in order to meet users’ needs and expectations. The authors propose a set of semantic descriptors based on both user physiological signals, captured while watching videos, and on video low-level features extraction. These XML based descriptors contribute to the creation of automatic affective meta-information that will not only enhance a web-based video recommendation system based in emotional information, but also enhance search and retrieval of videos affective content from both users’ personal classifications and content classifications in the context of a web portal.

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