Emotion related structures in large image databases
Proceedings of the ACM International Conference on Image and Video Retrieval
Horror image recognition based on emotional attention
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
Proceedings of the 2011 conference on Information Modelling and Knowledge Bases XXII
Proceedings of the 2011 conference on Information Modelling and Knowledge Bases XXII
Content based detection of popular images in large image databases
SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
Emotion based classification of natural images
Proceedings of the 2011 international workshop on DETecting and Exploiting Cultural diversiTy on the social web
Context-aware affective images classification based on bilayer sparse representation
Proceedings of the 20th ACM international conference on Multimedia
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In this paper we describe how to include high level semantic information, such as aesthetics and emotions, into Content Based Image Retrieval. We present a color-based emotion-related image descriptor that can be used for describing the emotional content of images. The color emotion metric used is derived from psychophysical experiments and based on three variables: activity, weight and heat. It was originally designed for single-colors, but recent research has shown that the same emotion estimates can be applied in the retrieval of multi-colored images. Here we describe a new approach, based on the assumption that perceived color emotions in images are mainly affected by homogenous regions, defined by the emotion metric, and transitions between regions. RGB coordinates are converted to emotion coordinates, and for each emotion channel, statistical measurements of gradient magnitudes within a stack of low-pass filtered images are used for finding interest points corresponding to homogeneous regions and transitions between regions. Emotion characteristics are derived for patches surrounding each interest point, and saved in a bag-of-emotions, that, for instance, can be used for retrieving images based on emotional content.