Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Affective computing
Possibility theory is not fully compositional!: a comment on a short note by H.J. Greenberg
Fuzzy Sets and Systems
Semantics in Visual Information Retrieval
IEEE MultiMedia
Semantic Annotation of Sports Videos
IEEE MultiMedia
Fuzzy-GIST for emotion recognition in natural scene images
DEVLRN '09 Proceedings of the 2009 IEEE 8th International Conference on Development and Learning
Hi-index | 0.00 |
In this paper, we propose a 3D fuzzy GIST to effectively describe the visual dynamic features related to the emotional characteristics in a movie clip. Unlike the previous fuzzy approaches, which use images, the proposed method employs movie clips and can dynamically extract the features to classify the emotional characteristics in a movie clip. The 3D fuzzy GIST based on 3D tensor data including L*C*H color (L: Lightness, C: Chroma, H: Hue) and orientation information in a movie clip can extract the visual dynamic features related to the emotional characteristics in a movie clip. The extracted visual dynamic features obtained by the proposed 3D fuzzy GIST are used as inputs to an adaptive neuro-fuzzy inference classifier. The classifier is provided with the mean opinion scores as the teaching signals. Experimental results show that the system with the proposed 3D fuzzy GIST feature extractor not only discriminates the positive emotional features from the negative ones but also identifies the changes of emotional features in movie clips successfully.