XCSF for prediction on emotion induced by image based on dimensional theory of emotion

Po Ming Lee*, Yun Teng, Tzu-Chien Hsiao

*此作品的通信作者

研究成果: Conference contribution同行評審

7 引文 斯高帕斯(Scopus)

摘要

Affective image classification problem is a problem aims on classifying images according to their affective characteristics of inducing human emotions. This paper extends the discrete state classification problem into a continuous function approximation problem by applying the experimental paradigm of dimensional emotion model. The Extended Classifier System for Function Approximation (XCSF) was applied to the problem and the results suggest that it outperforms linear regression (LR) in accomplishing this task. The obtained results also indicate that without using content based features of the images, the effects of individual difference can be relatively small.

原文English
主出版物標題GECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation Companion
頁面375-382
頁數8
DOIs
出版狀態Published - 20 八月 2012
事件14th International Conference on Genetic and Evolutionary Computation, GECCO'12 - Philadelphia, PA, United States
持續時間: 7 七月 201211 七月 2012

出版系列

名字GECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation Companion

Conference

Conference14th International Conference on Genetic and Evolutionary Computation, GECCO'12
國家/地區United States
城市Philadelphia, PA
期間7/07/1211/07/12

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