Correlating Eye Gaze with Object to Enrich Cultural Heritage Knowledge Graph

Virtual Reality (VR) technology has the potential to enhance cultural heritage experiences by providing immersive environments. This study proposes a novel approach that combines VR environments with eye-tracking data to identify users’ points of interest in exhibition paintings. By leveraging gaze patterns, valuable insights into user preferences, behavior, and attention can be extracted and integrated into the cultural heritage knowledge graph. To achieve this, an object detection model is fine-tuned on historical artwork datasets, and statistical tests are conducted to analyze gaze-object correlations. The results demonstrate the feasibility of using an object detection algorithm to detect points of interest and reveal correlations between eye gaze patterns and meaningful objects in paintings. This approach has the potential to enrich the knowledge graph, enabling more personalized and immersive experiences for art enthusiasts and visitors.