A natural language processing-based approach: mapping human perception by understanding deep semantic features in street view images
The study used a natural language model to understand deep semantic features in street view images to measure human perception of urban scenes. By combining image captioning with a fine-tuned BERT model, the researchers created a framework that outperformed previous methods using shallow image features. This approach offers better explanations for spatial differences in how people perceive city environments.