Evaluation of Features and Combination Approaches for the Classification of Emotional Semantics in Images

Ningning Liu 1 Emmanuel Dellandréa 1 Bruno Tellez 1 Liming Chen 1
1 imagine - Extraction de Caractéristiques et Identification
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : Recognition of emotional semantics in images is a new and very challenging research direction that gains more and more attention in the research community. As an emerging topic, publications remains relatively rare and numerous issues need to be addressed. In this paper, we propose to investigate the efficiency of different types of features including low-level features and proposed semantic features for classification of emotional semantics in images. Moreover, we propose a new approach that combines different classifiers based on Dempster-Shafer’s theory of evidence, which has the ability to handle ambiguous and uncertain knowledge such as the properties of emotions. Experiments driven on the International Affective Picture System (IAPS) image databases, which is a common stimulus set frequently used in emotion psychology research, demonstrated that the proposed approach can achieve promising results.
Document type :
Conference papers
Complete list of metadatas

https://hal.archives-ouvertes.fr/hal-01354394
Contributor : Équipe Gestionnaire Des Publications Si Liris <>
Submitted on : Thursday, August 18, 2016 - 7:25:36 PM
Last modification on : Wednesday, November 20, 2019 - 3:02:06 AM

Identifiers

  • HAL Id : hal-01354394, version 1

Citation

Ningning Liu, Emmanuel Dellandréa, Bruno Tellez, Liming Chen. Evaluation of Features and Combination Approaches for the Classification of Emotional Semantics in Images. International Conference on Computer Vision, Theory and Applications (VISAPP), Mar 2011, Vilamoura, Algarve, Portugal. pp.352-357. ⟨hal-01354394⟩

Share

Metrics

Record views

263