Biometric painting: Integrating biosensor data into the creative process
Abstract
Art has been a medium of self-expression, evolving with technological advancements. Using physiological signals, biometric painting directly affects the artistic process. By bridging the gap between the artist’s internal emotional state and the visual depiction of the painting, this fusion provides an innovative approach to examining and expressing human emotions. The objective is to investigate biometric painting, integrating biosensor data into the creative process. To expand the creative process of biometric painting by utilizing biosensor data to establish emotion recognition in biometric painting. A biometric painting system was created that used users’ real-time biosensor data to gather visual components that represented their emotional and physical states. The data is preprocessed using a median filter to remove noise from the sensor data. Then, the features are extracted using wavelet transform (WT). The research introduces an Intelligent Remora Optimized Flexible Deep Belief Network (IRO-FDBN) to recognize emotion in biometric painting using biosensor data. The results indicate that the established model outperforms an emotion recognition model. The approach emphasizes the smooth combination of visual and affective feedback, allowing audiences to engage with the artwork on an advanced level. This provides a foundation for incorporating biosensor data into the creative process, advancing artistic exploration and effective content development.
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