Combining Unmanned Aerial Vehicles, and Internet Protocol Cameras to Reconstruct 3-D Disaster Scenes During Rescue Operations.

Objective: Strong earthquakes often cause massive structural and nonstructural damage, timely assessment of the catastrophe related massive casualty incidents (MCIs) for deploying rescue resource are critical in order to minimize ongoing fatalities. A magnitude 6.6 earthquake struck southern Taiwan on February 6, 2016 (the so-called 02/06 Meinong earthquake). It led to 117 deaths and 522 injuries. Advanced technologies including aerial devices and innovation concept were adopted for more effective rescue efforts. We would like to share our innovative concept in MCIs experienced in 02/06 Meinong earthquake in 2016. Methods: A collapsed building, Weiguan residential apartment complex, was the most devastating building collapsed in Tainan, resulting in 115 people killed. Regional Emergency Medical Operational Centers (REMOCs), supervised by Taiwan Ministry of Health and Welfare, were activated immediately and collaborated with Tainan City government command center to initiate emergency rescue reliefs. Results: We, for the first time, attempted to use cyber devices including an internet-protocol camera and a multi-rotor unmanned aerial vehicle (UAV) equipped with a high-resolution digital camera used to acquire imagery during the rescue operation. Moreover, a photo-realistic 3-D model reconstructed by the acquired UAV imagery could provide real-time information from UAV to rescue team leaders in remote location for effectively deploying medical posts and emergency resources at scene. Conclusion: We proposed the concept of real-time UAV imagery for reconstructing photo-realistic 3-D model, which might greatly improve prehospital emergency management after disaster.

A semi-automatic image-based close range 3D modeling pipeline using a multi-camera configuration.

The generation of photo-realistic 3D models is an important task for digital recording of cultural heritage objects. This study proposes an image-based 3D modeling pipeline which takes advantage of a multi-camera configuration and multi-image matching technique that does not require any markers on or around the object. Multiple digital single lens reflex (DSLR) cameras are adopted and fixed with invariant relative orientations. Instead of photo-triangulation after image acquisition, calibration is performed to estimate the exterior orientation parameters of the multi-camera configuration which can be processed fully automatically using coded targets. The calibrated orientation parameters of all cameras are applied to images taken using the same camera configuration. This means that when performing multi-image matching for surface point cloud generation, the orientation parameters will remain the same as the calibrated results, even when the target has changed. Base on this invariant character, the whole 3D modeling pipeline can be performed completely automatically, once the whole system has been calibrated and the software was seamlessly integrated. Several experiments were conducted to prove the feasibility of the proposed system. Images observed include that of a human being, eight Buddhist statues, and a stone sculpture. The results for the stone sculpture, obtained with several multi-camera configurations were compared with a reference model acquired by an ATOS-I 2M active scanner. The best result has an absolute accuracy of 0.26 mm and a relative accuracy of 1:17,333. It demonstrates the feasibility of the proposed low-cost image-based 3D modeling pipeline and its applicability to a large quantity of antiques stored in a museum.

Direct sensor orientation of a land-based mobile mapping system.

A land-based mobile mapping system (MMS) is flexible and useful for the acquisition of road environment geospatial information. It integrates a set of imaging sensors and a position and orientation system (POS). The positioning quality of such systems is highly dependent on the accuracy of the utilized POS. This limitation is the major drawback due to the elevated cost associated with high-end GPS/INS units, particularly the inertial system. The potential accuracy of the direct sensor orientation depends on the architecture and quality of the GPS/INS integration process as well as the validity of the system calibration (i.e., calibration of the individual sensors as well as the system mounting parameters). In this paper, a novel single-step procedure using integrated sensor orientation with relative orientation constraint for the estimation of the mounting parameters is introduced. A comparative analysis between the proposed single-step and the traditional two-step procedure is carried out. Moreover, the estimated mounting parameters using the different methods are used in a direct geo-referencing procedure to evaluate their performance and the feasibility of the implemented system. Experimental results show that the proposed system using single-step system calibration method can achieve high 3D positioning accuracy.