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Title |
Transfer Learning for Face Emotions Recognition in Different Crowd Density Situations |
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Author |
Amirah Alharbi |
| Citation |
Vol. 24 No. 4 pp. 26-34 |
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Abstract |
Most human emotions are conveyed through facial expressions, which represent the predominant source of emotional data. This research investigates the impact of crowds on human emotions by analysing facial expressions. It examines how crowd behaviour, face recognition technology, and deep learning algorithms contribute to understanding the emotional change according to different level of crowd. The study identifies common emotions expressed during congestion, differences between crowded and less crowded areas, changes in facial expressions over time. The findings can inform urban planning and crowd event management by providing insights for developing coping mechanisms for affected individuals. However, limitations and challenges in using reliable facial expression analysis are also discussed, including age and context-related differences. |
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Keywords |
facial expressions; crowd; crowd management; emotions; bias. |
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