No single sensor can acquire complete information by applying one or several multi-surveys to cultural object reconstruction. For instance, a terrestrial laser scanner (TLS) usually obtains information on building facades, whereas aerial photogrammetry is capable of providing the perspective for building roofs. In this study, a camera-equipped unmanned aerial vehicle system (UAV) and a TLS were used in an integrated design to capture 3D point clouds and thus facilitate the acquisition of whole information on an object of interest for cultural heritage. A camera network is proposed to modify the image-based 3D reconstruction or structure from motion (SfM) method by taking full advantage of the flight control data acquired by the UAV platform. The camera network improves SfM performances in terms of image matching efficiency and the reduction of mismatches. Thus, this camera network modified SfM is employed to process the overlapping UAV image sets and to recover the scene geometry. The SfM output covers most information on building roofs, but has sparse resolution. The dense multi-view 3D reconstruction algorithm is then applied to improve in-depth detail. The two groups of point clouds from image reconstruction and TLS scanning are registered from coarse to fine with the use of an iterative method. This methodology has been tested on one historical monument in Fujian Province, China. Results show a final point cloud with complete coverage and in-depth details. Moreover, findings demonstrate that these two platforms, which integrate the scanning principle and image reconstruction methods, can supplement each other in terms of coverage, sensing resolution, and model accuracy to create high-quality 3D recordings and presentations.

This paper investigates the synergetic use of unmanned aerial vehicle (UAV) and terrestrial laser scanner (TLS) in 3D reconstruction of cultural heritage objects. Rather than capturing still images, the UAV that equips a consumer digital camera is used to collect dynamic videos to overcome its limited endurance capacity. Then, a set of 3D point-cloud is generated from video image sequences using the automated structure-from-motion (SfM) and patch-based multi-view stereo (PMVS) methods. The TLS is used to collect the information that beyond the reachability of UAV imaging e.g., partial building facades. A coarse to fine method is introduced to integrate the two sets of point clouds UAV image-reconstruction and TLS scanning for completed 3D reconstruction. For increased reliability, a variant of ICP algorithm is introduced using local terrain invariant regions in the combined designation. The experimental study is conducted in the Tulou culture heritage building in Fujian province, China, which is focused on one of the TuLou clusters built several hundred years ago. Results show a digital 3D model of the Tulou cluster with complete coverage and textural information. This paper demonstrates the usability of the proposed method for efficient 3D reconstruction of heritage object based on UAV video and TLS data.