Minimal Camera Networks for 3D Image Based Modeling of Cultural Heritage Objects

3D modeling of cultural heritage objects like artifacts, statues and buildings is nowadays an important tool for virtual museums, preservation and restoration. In this paper, we introduce a method to automatically design a minimal imaging network for the 3D modeling of cultural heritage objects. This becomes important for reducing the image capture time and processing when documenting large and complex sites. Moreover, such a minimal camera network design is desirable for imaging non-digitally documented artifacts in museums and other archeological sites to avoid disturbing the visitors for a long time and/or moving delicate precious objects to complete the documentation task. The developed method is tested on the Iraqi famous statue “Lamassu”. Lamassu is a human-headed winged bull of over 4.25 m in height from the era of Ashurnasirpal II (883–859 BC). Close-range photogrammetry is used for the 3D modeling task where a dense ordered imaging network of 45 high resolution images were captured around Lamassu with an object sample distance of 1 mm. These images constitute a dense network and the aim of our study was to apply our method to reduce the number of images for the 3D modeling and at the same time preserve pre-defined point accuracy. Temporary control points were fixed evenly on the body of Lamassu and measured by using a total station for the external validation and scaling purpose. Two network filtering methods are implemented and three different software packages are used to investigate the efficiency of the image orientation and modeling of the statue in the filtered (reduced) image networks. Internal and external validation results prove that minimal image networks can provide highly accurate records and efficiency in terms of visualization, completeness, processing time (>60% reduction) and the final accuracy of 1 mm

Potential Use of Drone Ultra-High-Definition Videos for Detailed 3D City Modeling

Ongoing developments in video resolution either using consumer-grade or professional cameras has opened opportunities for different applications such as in sports events broadcasting and digital cinematography. In the field of geoinformation science and photogrammetry, image-based 3D city modeling is expected to benefit from this technology development. Highly detailed 3D point clouds with low noise are expected to be produced when using ultra high definition UHD videos (e.g., 4K, 8K). Furthermore, a greater benefit is expected when the UHD videos are captured from the air by consumer-grade or professional drones. To the best of our knowledge, no studies have been published to quantify the expected outputs when using UHD cameras in terms of 3D modeling and point cloud density. In this paper, a quantification is shown about the expected point clouds and orthophotos qualities when using UHD videos from consumer-grade drones and a review of which applications they can be applied in. The results show that an improvement in 3D models of ≅65% relative accuracy and ≅90% in point density can be attained when using 8K video frames compared with HD video frames which will open a wide range of applications and business cases in the near future

Prospects of Consumer-Grade UAVs for Overpass Bridges Pier Pads Alignment

The use of Unmanned Aerial Vehicles (UAVs) for surveying is at the forefront of their use in the Architectural Engineering and Construction (AEC) industry. UAVs make accessing hard-to-reach construction regions simpler and more cost-effective because of their small size, ease of mobility, and the wealth of information given by their integrated sensors. Accordingly, their use is thriving in different AEC sectors such as the management and inspection of engineering facilities such as concrete bridges. Overpass bridge engineering inspections are still applied using high accuracy surveying instruments in situ to ensure meeting the quality standards of construction. One important application is to measure the bridge pier caps centerline fitting using total stations, which is costly in terms of time and labor. Therefore, in this article, a new approach based on consumer-grade UAV imaging is proposed for replacing the traditional surveying techniques which are expected to improve automation and reduce time and cost. The proposed method utilized a sequence of processes on the UAV point clouds of the bridge concrete pier caps to finally extract the pier pads center and check their alignment. In two experiments, point clouds are created using DJI Phantom 3 images taken over bridge pier projects under construction, and concrete pad centers are then estimated and compared to the reference total station measurements. The results of both tests reveal the ability of the proposed method to attain the required accuracy for the pads’ alignment, as the root mean square error (RMSE) is one centimeter and two centimeters for the first and second tests, respectively. In addition, the new approach can reduce implementation time and the project budget

UAV Remote Sensing for Smart Agriculture

As the world population continues to grow, the demand for food is also increasing. At the same time, a series of global and local challenges are threatening ‘food security’. In this context, various technologies and techniques have been proposed and considered in recent decades to secure the efficient usage of the planet’s agricultural resources, i.e. ‘smart agriculture’. This requires the accurate and advanced acquisition, modelling and management of relevant data. This article presents a brief discussion of how unmanned aerial vehicles (UAVs or ‘drones’) can play a critical role in smart agriculture, including a focus on their capabilities and applications

Out of Plumb Assessment for Cylindrical-Like Minaret Structures Using Geometric Primitives Fitting

Cultural heritage documentation and monitoring represents one of the major tasks for experts in the field of surveying, photogrammetry and geospatial engineering. Cultural heritage objects in countries like Iraq and Syria have suffered from intentional destruction or demolition during the last few years. Furthermore, many heritage sites in the mentioned places have an added religious value, and were either destroyed or are still in danger. Mosques, churches and shrines typically include one or multiple tower structures, and these towers or minarets are in many cases cylindrical-like objects. Because of their tall and relatively thin body, and adding in their age of construction, observing their inclination or out of plumb is of high importance. Accordingly, it is highly necessary for the continuous monitoring and assessment of their preservation and restoration. In this paper, we suggest an out of plumb assessment procedure using a geometric primitives least squares fitting technique, namely, cylinders, cones, and 3D circles. The approach is based on reconstructing a dense point cloud of the minaret tower which is scaled to reality by control points. Accordingly, the out of plumb is computed by fitting one of the mentioned 3D primitives to the minaret point cloud where its major axis orientation is computed. Two experimental tests of heritage objects in Iraq are presented: the lost heritage of the minaret al Hadbaa in the city of Mosul (1173 AD) and an existing inclined minaret of the religious shrine of Imam Musa AlKadhim in Baghdad (1058 AD). The results show the efficiency of the suggested methodology where the out of plumb is computed as 0.45m±1cm for the shrine minaret and 1.90m±10cm for the model of the minaret al Hadbaa

Efficient Flight Planning For Building Façade 3D Reconstruction

Three-dimensional (3D) building model is gaining more scientific attention in recent times due to its application in various fields such as vehicle autonomous navigation, urban planning, heritage building documentation, gaming visualisation and tourism. The quality of the Level of Detail (LoD) of building models relies on the high-resolution data sets obtained for the building. As an alternative to laser scanners, Unmanned Aerial Vehicles (UAV) are efficient in collecting good quality images and generate reliable LoD3 of buildings (i.e. to model both roof and facades of a building) at comparatively lower cost and time. However, the complete collection of images on building facades is usually performed by manual flights along the different façade to assure a homogenous image coverage with the same resolution on each element: no offline autonomous procedure to define the main façade planes and acquire complete image sets independent of UAV platform have been developed yet. This paper proposes a novel methodology to generate the flight plan in correspondence of building facades. The Digital Surface Model (DSM) obtained from an initial nadir flight is used as an input to identify the target building and plan the image acquisition around it. The optimised flight plan ensures complete coverage of the building with a minimum number of images. The coordinates as well as the attitude of each planned image can be finally loaded on a UAV to perform the flight. In order to validate the proposed methodology, some tests performed on synthetic buildings of growing complexity and very different shapes are presented

Minimal Camera Networks for 3D Image Based Modeling of Cultural Heritage Objects

3D modeling of cultural heritage objects like artifacts, statues and buildings is nowadays an important tool for virtual museums, preservation and restoration. In this paper, we introduce a method to automatically design a minimal imaging network for the 3D modeling of cultural heritage objects. This becomes important for reducing the image capture time and processing when documenting large and complex sites. Moreover, such a minimal camera network design is desirable for imaging non-digitally documented artifacts in museums and other archeological sites to avoid disturbing the visitors for a long time and/or moving delicate precious objects to complete the documentation task. The developed method is tested on the Iraqi famous statue “Lamassu”. Lamassu is a human-headed winged bull of over 4.25 m in height from the era of Ashurnasirpal II (883–859 BC). Close-range photogrammetry is used for the 3D modeling task where a dense ordered imaging network of 45 high resolution images were captured around Lamassu with an object sample distance of 1 mm. These images constitute a dense network and the aim of our study was to apply our method to reduce the number of images for the 3D modeling and at the same time preserve pre-defined point accuracy. Temporary control points were fixed evenly on the body of Lamassu and measured by using a total station for the external validation and scaling purpose. Two network filtering methods are implemented and three different software packages are used to investigate the efficiency of the image orientation and modeling of the statue in the filtered (reduced) image networks. Internal and external validation results prove that minimal image networks can provide highly accurate records and efficiency in terms of visualization, completeness, processing time (>60% reduction) and the final accuracy of 1 mm