Affective computing
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
2005 Special Issue: A systems approach to appraisal mechanisms in emotion
Neural Networks - Special issue: Emotion and brain
2005 Special Issue: A systems approach to appraisal mechanisms in emotion
Neural Networks - Special issue: Emotion and brain
Automatic textile image annotation by predicting emotional concepts from visual features
Image and Vision Computing
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Audio-Visual Affect Recognition
IEEE Transactions on Multimedia
A domain-independent framework for modeling emotion
Cognitive Systems Research
Cellular Neural Networks, the Navier–Stokes Equation, and Microarray Image Reconstruction
IEEE Transactions on Image Processing
Fuzzy Similarity-Based Emotional Classification of Color Images
IEEE Transactions on Multimedia
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Several emotion eliciting models have been proposed in the literature, however most of them are still artificial models which ignore the biological basis. We propose an emotion (without awareness) eliciting model from visual stimuli, which is inspired by biology: we describe an emotion eliciting process that follows the circuits of emotion in the brain derived through the results of neuroscience and the three major modules in the process, visual perception, emotion-eliciting region and emotional valence elicited by the region, are all supported by biology research. In our work, visual perception works with visual stimuli from coarse to the finer level according to human visual system. The elicited emotion in coarse level is also capable of affecting the emotion valence in the finer level. Based on psychophysical research, the emotion-eliciting region is selected out through color preference. The emotion is elicited by the emotion-eliciting region rather than overall visual context, which has been first introduced to computational modeling of emotion eliciting from image stimuli. The emotional valence elicited by the region is calculated on coarseness and directionality by comparing with stored image representations. In the experiments, two types of visual stimuli are considered: (1) natural scenes stimuli and (2) natural scenes and mutilation scenes stimuli. We compare the performance of our model with International Affective Picture System (IAPS), a large set of emotionally evocative color photographs that includes pleasure and arousal ratings made by men and women. Experimental results show that our model can generate human-like emotion based on natural scenes stimuli and obtain the positive or negative emotion as people feel on natural scenes and mutilation scenes stimuli.