Storing ancient Buddha images in the form of 3D virtual objects with the photogrammetry technique for conservation

Abstract

This article presents a method for digitally storing ancient Buddha statues in a lifelike three-dimensional (3D) virtual form using photogrammetry techniques. The goal is preservation, achieved by creating a 3D virtual representation of ancient Buddha statues through digital photography. The process involves capturing images using a digital camera with a fixed focal length lens of 30 millimeters and a resolution of 24 megapixels. The captured images are then edited using Adobe Lightroom software and processed to generate a 3D model using reality capture software on a Windows operating system. The computer used for processing requires specialized image processing units and backup memory to support 3D image processing. The author selects specific ancient Buddha statues, focusing on detailed ivory-carved Buddhist sculptures, as a prototype for creating an image dataset. The photography takes place in two different areas: an outdoor location to utilize natural sunlight for lighting and a shaded area with low light conditions, where continuous studio lighting with a white light source is used. This allows for a quality comparison of the resulting photographs. The photography process ensures overall sharpness of the images with three levels of perspective: lower, middle, and upper, to establish interconnected points between images. The results of creating a 3D virtual model using photogrammetry techniques and reality capture software show that a lifelike 3D representation of an object can be achieved with a sufficient amount of light during outdoor photography. The quality of the 3D virtual model is significantly better than when capturing images in low-light conditions where noise can disrupt the reality capture software's calculations, resulting in an incomplete 3D representation. Therefore, to digitally preserve ancient Buddha statues in a lifelike 3D virtual form using photogrammetry techniques, it is crucial to have a dataset of clear and noise-free images for accurate and highly realistic 3D rendering.