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Updated: Jun 14, 2025

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EmotionCast: An Emotion-Driven Intelligent Broadcasting System for Dynamic Camera Switching.

Xinyi Zhang1, Xinran Ba1, Feng Hu1

  • 1School of Information and Communication Engineering, Communication University of China, Beijing 100024, China.

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|August 29, 2024
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Summary

This study introduces EmotionCast, an intelligent broadcasting system that uses emotion recognition to improve camera switching during live events. EmotionCast enhances audience engagement and satisfaction by making decisions based on real-time emotional dynamics.

Keywords:
emotion recognitionintelligent broadcastingmultimodal data processing

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Broadcasting Technology

Background:

  • Traditional broadcasting faces challenges with fatigue and errors in complex live content.
  • Current intelligent broadcasting systems lack the ability to understand emotional dynamics.

Purpose of the Study:

  • To develop an emotion-driven intelligent broadcasting system, EmotionCast.
  • To enhance camera switching efficiency during live broadcasts using multimodal emotion recognition.

Main Methods:

  • Collected real-time video and audio data using sensing technologies.
  • Employed deep learning for facial expression and vocal tone analysis to detect emotions.
  • Integrated visual, audio, and textual analyses to generate an emotional score for each camera shot.

Main Results:

  • EmotionCast demonstrated superior switching accuracy and emotional resonance.
  • The system significantly improved audience satisfaction and emotional engagement.
  • Experimental results confirmed enhanced performance compared to traditional methods.

Conclusions:

  • EmotionCast effectively addresses limitations in traditional and current intelligent broadcasting.
  • The system offers a novel approach to dynamic camera switching based on emotional cues.
  • EmotionCast has broad applicability in live event broadcasting, including sports, concerts, and performances.