Region-Guided Interactive Docent for Paintings in Mixed Reality

Abstract

We propose a system that provides personalized interpretation of physical paintings using an AR cursor in a mixed reality (MR) environment. In galleries, pointing at specific regions of complex paintings is often restricted, making it hard to ask targeted questions. While prior works have proposed interactive systems to assist visitor understanding, they typically offered generalized explanations that were not grounded in real, physically exhibited artworks. To address this gap, our approach allows users to intuitively drag across the surface of a painting using a hand-guided AR cursor to specify a Region of Interest. The cropped image, along with the user’s spoken question, is then sent to a Vision Language Model (VLM), which generates a personalized and context-aware explanation based on the selected area. This approach enables users to gain a more precise and meaningful understanding of the painting, guided by their specific interests.