Emotional Recognition Edge Computing Model for Emotion Classification with Immersive Theatre Experience
Keywords:
Emotion Recognition, Optimal Model, Edge Computing, Deep Learning, Probability ModelAbstract
Emotion recognition refers to the process of identifying and analyzing human emotions based on various cues, such as facial expressions, vocal intonations, gestures, and physiological responses. This technology utilizes machine learning algorithms and artificial intelligence techniques to interpret these cues and classify the emotions being expressed, which can include happiness, sadness, anger, fear, surprise, and more nuanced emotional states. An immersive theatre interactive experience is a unique and dynamic form of entertainment that transcends traditional passive spectatorship by fully engaging the audience through sensory stimulation, participation, and interaction. This paper presents an innovative framework, the Optimal Edge Computing Probability (OECP) model, designed to assess and enhance the immersive theatre interactive experience through the integration of an emotion recognition algorithm. With the power of edge computing, the OECP model dynamically allocates computational tasks between edge devices and centralized cloud resources. Through a comprehensive evaluation within the context of immersive theatre, the model optimally determines when to process emotion recognition data locally on edge devices and when to offload to the cloud. Simulation results demonstrate the model's effectiveness in accurately classifying a range of user emotions, yielding high classification accuracy, precision, recall, and F1-score values. This model not only ensures real-time responsiveness and efficient resource utilization but also opens new horizons for the intersection of emotion recognition, immersive experiences, and edge computing. As technological landscapes continue to evolve, the OECP model offers a robust foundation for refining user engagement and enriching the convergence of emotion analysis and interactive technologies.
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