On the link between emotion, attention and content in virtual immersive environments
2022 IEEE International Conference on Image Processing (ICIP), 2022•ieeexplore.ieee.org
While immersive media have been shown to generate more intense emotions, saliency
information has been shown to be a key component for the assessment of their quality,
owing to the various portions of the sphere (viewports) a user can attend. In this article, we
investigate the tri-partite connection between user attention, user emotion and visual content
in immersive environments. To do so, we present a new dataset enabling the analysis of
different types of saliency, both low-level and high-level, in connection with the user's state …
information has been shown to be a key component for the assessment of their quality,
owing to the various portions of the sphere (viewports) a user can attend. In this article, we
investigate the tri-partite connection between user attention, user emotion and visual content
in immersive environments. To do so, we present a new dataset enabling the analysis of
different types of saliency, both low-level and high-level, in connection with the user's state …
While immersive media have been shown to generate more intense emotions, saliency information has been shown to be a key component for the assessment of their quality, owing to the various portions of the sphere (viewports) a user can attend. In this article, we investigate the tri-partite connection between user attention, user emotion and visual content in immersive environments. To do so, we present a new dataset enabling the analysis of different types of saliency, both low-level and high-level, in connection with the user’s state in 360 ◦ videos. Head and gaze movements are recorded along with self-reports and continuous physiological measurements of emotions. We then study how the accuracy of saliency estimators in predicting user attention depends on user-reported and physiologically-sensed emotional perceptions. Our results show that high-level saliency better predicts user attention for higher levels of arousal. We discuss how this work serves as a first step to understand and predict user attention and intents in immersive interactive environments.
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