Discovering latent semantic factors for emotional picture categorization

Shuo Li*, Yu Jin Zhang, Hua Chun Tan

*Corresponding author for this work

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

11 Citations (Scopus)

Abstract

How to teach computer to classify pictures into different emotional categories automatically as humans? It is a quite interesting and challenging research direction. This paper defines the latent emotional semantic factors and proposes a novel approach for emotional picture categorization. Unlike traditional methods, the latent emotional semantic factor is defined for representing the middle level semantic concept, and it can effectively bridge the "semantic gap". In the experiments made on the International Affective Picture System (IAPS) [1-4], the proposed approach for emotional picture categorization distinctly outperforms the latest method.

Original languageEnglish
Title of host publication2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
Pages1065-1068
Number of pages4
DOIs
Publication statusPublished - 2010
Event2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, Hong Kong
Duration: 26 Sept 201029 Sept 2010

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Conference

Conference2010 17th IEEE International Conference on Image Processing, ICIP 2010
Country/TerritoryHong Kong
CityHong Kong
Period26/09/1029/09/10

Keywords

  • Emotional picture categorization
  • Latent emotional semantic factors
  • Semantic gap

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