![]() ![]() ![]() ![]() The experiments concerned cuneiform tablets, which are challenging due to their morphological and geometrical characteristics. In this context, this research aims to meet the demand for a digital survey and 3D representation of small objects with complex surfaces and sub-millimeter morphological characteristics using a low-cost configuration (passive sensors) for an image-based approach. In the current panorama of 3D digital documentation, the survey of tiny artifacts with micrometric details is strongly influenced by two factors: firstly, the still high cost of the instruments and technologies (active sensors) required to achieve the necessary level of accuracy and resolution secondly, the needed professional skills for the macro-photogrammetric approach. Experiments shows that the proposed technique can be easily performed on the field with a resulting RTI model that can outperform state-of-the-art approaches involving dedicated hardware setups. ![]() To deal with such amount of data, we propose a neural relighting model that reconstructs object appearance for arbitrary light directions from extremely compact reflectance distribution data compressed via Principal Components Analysis (PCA). Since the led is mounted close to the camera lenses, we can infer the light direction for thousands of images by freely moving the illuminating device while observing a fiducial marker surrounding the subject. The flash led-light of one device is used to illuminate the subject while the other captures the reflectance. We propose a novel RTI method that can be carried out by recording videos with two ordinary smartphones. Such process, however, typically requires dedicated hardware setups to recover the light direction from multiple locations, making the process tedious when performed outside the lab. This can be later used to reveal surface details and interactively relight the subject. Reflectance Transformation Imaging (RTI) is a popular technique that allows the recovery of per-pixel reflectance information by capturing an object under different light conditions. These benefits over current standards of best practice can be generalized to a broad range of cultural heritage material. Collaborative tests between Cultural Heritage Imaging, Hewlett- Packard Labs, and the UNESCO Prehistoric Rock-Art Sites in the Côa Valley, a World Heritage Site in Portugal, suggest this approach will be very beneficial when applied to paleolithic petroglyphs of various sizes, both in the field and in the laboratory. It permits RTI examination "in the round" in a unified, interactive, image-based representation. A complementary method of integrating digital RTI representations of subjects from multiple viewpoints is also presented. The acquisition method is simple, fast, very low cost, and easy to learn. Unlike existing PTM capture methods requiring known light source positions, we rely on the user to position a handheld light source, and recover the lighting direction from the specular highlights produced on a black sphere included in the field of view captured by the camera. One imaging method is able to acquire Polynomial Texture Maps (PTMs) of 3D rock art possessing a large range of sizes, shapes, and environmental contexts. We offer two new methods of documenting and communicating cultural heritage information using Reflection Transformation Imaging (RTI). ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |