Three dimensional (3D) scanned point clouds offer an invaluable tool for the digital preservation of cultural heritage, capturing intricate and complex 3D structures. Transparent visualization, i.e., see-through visualization, is essential for effectively understanding these data. However, since 3D scanned point clouds do not include normal vector information, applying shading effects to reveal complex shapes is challenging. In this paper, we present a method for assigning normal vectors to 3D scanned points using a statistical approach based on principal component analysis. To resolve the ambiguity of normal vector orientations, specifically the front or back of local surfaces, we exploit the characteristics of transparent visualization. Each normal vector is oriented toward the viewpoint, enabling consistent shading across all visible points. We then apply dynamic shading by varying the light source position sequentially, which highlights different regions of the visualized object. This approach allows for a shift in focus between surface features and deeper internal structures, enhancing the understanding of the overall structure of complex 3D cultural heritage objects. We demonstrate the effectiveness of dynamic shading through its application to real 3D scanned data of cultural heritage objects with intricate internal structures.

We propose a new application of stochastic point-based rendering, which was recently proposed for implicit surfaces, to large-scale laser-scanned 3D point data. Specifically, we propose a scheme to apply the rendering to transparent and fused visualization of recent large and complex laser-scanned data from cultural assets. Our scheme uses 3D points that are directly acquired using a laser scanner as the rendering primitives. For laser-scanned data that consist of more than 107 or 108 3D points, the pre-processing stage takes only a few minutes, and the rendering stage is executable at interactive frame rates. We do not encounter rendering artifacts originating from the indefiniteness of depth-sorted orders of rendering primitives. Fused visualization with various visual assistants is also possible. We demonstrate the effectiveness of our scheme by visualizing a campus building and a culturally important festival float.