# GNSS-Assisted Low-Cost Vision-Based Observation System for Deformation Monitoring
###### Abstract
The computer vision approach focuses chiefly on different image refinement methods, a digital correlation between images, etc. Math models for geometric information extraction are less strict but more robust. Computer vision approaches have become very popular thanks to their high robustness and automation [44; 45; 46; 47; 48; 49; 50; 51; 52; 53; 54; 55; 56; 57; 58]. Let us analyze some of them with unique features regarding the study goal. The study [44] considers computer vision methods tested on a four-story steel frame in lab conditions. These methods comprise the optical flow with the Lucas-Kanade method, the digital image correlation with bilinear interpolation, and the phase-based motion magnification using the Reisz pyramid. The authors of [46; 47] developed a novel sensor for displacement measurements using one camera. They suggested an advanced template-matching algorithm. Paper [48] compares two noncontact measurement methods: the vision-based method underpinned by image correlation and the radar interferometer. The vision-based system uses one or two cameras mounted on a tripod. The paper [51] proposes an approach based on measurements of retro-reflective targets, while [52] offers the same approach free of targets. In [53; 54], the vision-based monitoring task is considered as a problem of the best methods and algorithms for image compression and processing under dark-light conditions. It is worth noting that the computer vision approach can also be used for vibration measurements, as claimed in [55]. The study was conducted in a lab environment. In virtue of the high level of automation, the computer vision approach can be fused with other sensors, e.g., the fusion between a vision-based system and accelerometers. Another sample of integration is [58], where computer vision technology is integrated with terrestrial laser scanning. For all the considered cases, the measurements are based on one or two cameras, without external reference to some stable basis, insofar as the detected displacements are relative and do not present the total (global) structure deformation. The discussion about monitoring will not be comprehensive without the small sensors mentioned. These sensors have recently become one of GNSS's main integration elements. These sensors supplement GNSS and ensure good results for monitoring high-rise buildings. Among the different measuring sensors, it is worth mentioning the following ones that determine structure deformation and their applications, e.g., inclinometers [59; 60] to detect inclinations in a particular direction, high-resolution lasers [61; 62], tilt meters [63] to measure plane inclination, low-cost radars [64], and 3-D inclinometers [65] to determine a spatial rotation. A set of papers and reports give an overall review regarding the use of various sensors [66; 67; 68; 69; 70]. Whatever sensor is used, it provides superior accuracy. Still, the main drawback is the need to organize them into one system and reference this system to some external coordinate system because any sensor provides relative displacements. Despite the importance of deformation monitoring, this task is just a small unit of a more significant problem. The technologies mentioned above have become a part of a giant branch named structural health monitoring (SHM). Structural health monitoring has become a pretty widespread problem recently. This problem is highly complex and comprises many methods and technologies to monitor a massive range of various building parameters. Therefore, any vision-based low-cost video observation system should become an integrated part of the SHM system. Many papers regarding this problem have been published recently [71; 72; 73; 74; 75; 76; 77; 78; 79]. A subject of SHM can be temperature variation inside and outside of a structure, air conditioning, humidity inside or underlying soils, and the status of various structure elements, e.g., cracks, damages, and so on. One of the essential applications of SHM is structure deformation monitoring.