SIFT-Based Depth Estimation for Accurate 3D Reconstruction in Cultural Heritage Preservation

This paper describes a proposed method for preserving tangible cultural heritage by reconstructing a 3D model of cultural heritage using 2D captured images. The input data represent a set of multiple 2D images captured using different views around the object. An image registration technique is applied to configure the overlapping images with the depth of images computed to construct the 3D model. The automatic 3D reconstruction system consists of three steps: (1) Image registration for managing the overlapping of 2D input images; (2) Depth computation for managing image orientation and calibration; and (3) 3D reconstruction using point cloud and stereo-dense matching. We collected and recorded 2D images of tangible cultural heritage objects, such as high-relief and round-relief sculptures, using a low-cost digital camera. The performance analysis of the proposed method, in conjunction with the generation of 3D models of tangible cultural heritage, demonstrates significantly improved accuracy in depth information. This process effectively creates point cloud locations, particularly in high-contrast backgrounds.