Global-local attention for emotion recognition

Unlocking the Emotional World of Visual Media: An Overview of the Science, Research, and Impact of Understanding Emotion: Drawing Insights From Psychology, Engineering, and the Arts, This Article Provides a Comprehensive Overview of the Field of Emotion Analysis in Visual Media and Discusses the Latest Research, Systems, Challenges, Ethical Implications, and Potential Impact of Artificial Emotional Intelligence on Society

The emergence of artificial emotional intelligence technology is revolutionizing the fields of computers and robotics, allowing for a new level of communication and understanding of human behavior that was once thought impossible. While recent advancements in deep learning have transformed the field of computer vision, automated understanding of evoked or expressed emotions in visual media remains in its infancy. This foundering stems from the absence of a universally accepted definition of "emotion," coupled with the inherently subjective nature of emotions and their intricate nuances. In this article, we provide a comprehensive, multidisciplinary overview of the field of emotion analysis in visual media, drawing on insights from psychology, engineering, and the arts. We begin by exploring the psychological foundations of emotion and the computational principles that underpin the understanding of emotions from images and videos. We then review the latest research and systems within the field, accentuating the most promising approaches. We also discuss the current technological challenges and limitations of emotion analysis, underscoring the necessity for continued investigation and innovation. We contend that this represents a "Holy Grail" research problem in computing and delineate pivotal directions for future inquiry. Finally, we examine the ethical ramifications of emotion-understanding technologies and contemplate their potential societal impacts. Overall, this article endeavors to equip readers with a deeper understanding of the domain of emotion analysis in visual media and to inspire further research and development in this captivating and rapidly evolving field.

Diminished emotion recognition with reduced face gaze in complex situation in individuals with broad autism phenotype

Background/objective

Individuals with broad autism phenotype (BAP) showed a diminished ability to recognize emotion. This study aims to examine whether their decline in emotion recognition ability could be more clearly identified as task complexity increased and whether their decline could be influenced by their eye-gaze patterns.

Method

41 individuals with BAP and 40 healthy controls performed two types of emotion recognition tasks. After confirming conditions wherein the BAP group did not perform well compared to the control group, we compared gaze proportion on faces and context between groups when performing the conditions.

Results

The more difficult the task, the clearer the significant relationships between the level of autistic traits and emotion recognition ability. The BAP group showed lower accuracy compared to the control group when a face with mild emotional intensity was presented with context. In terms of gaze proportion, the BAP group looked less at faces when recognizing emotions compared to the control group.

Conclusion

These findings indicate that diminished emotion recognition ability in individuals with BAP may be influenced by face gaze.