Structural health monitoring at local and global levels using computer vision technologies has gained much attention in the structural health monitoring community in research and practice. Due to the computer vision technology application advantages such as non-contact, long distance, rapid, low cost and labor, and low interference to the daily operation of structures, it is promising to consider computer vision–structural health monitoring as a complement to the conventional structural health monitoring. This article presents a general overview of the concepts, approaches, and real-life practice of computer vision–structural health monitoring along with some relevant literature that is rapidly accumulating. The computer vision–structural health monitoring covered in this article at local level includes applications such as crack, spalling, delamination, rust, and loose bolt detection. At the global level, applications include displacement measurement, structural behavior analysis, vibration serviceability, modal identification, model updating, damage detection, cable force monitoring, load factor estimation, and structural identification using input–output information. The current research studies and applications of computer vision–structural health monitoring mainly focus on the implementation and integration of two-dimensional computer vision techniques to solve structural health monitoring problems and the projective geometry methods implemented are utilized to convert the three-dimensional problems into two-dimensional problems. This review mainly puts emphasis on two-dimensional computer vision–structural health monitoring applications. Subsequently, a brief review of representative developments of three-dimensional computer vision in the area of civil engineering is presented along with the challenges and opportunities of two-dimensional and three-dimensional computer vision–structural health monitoring. Finally, the article presents a forward look to the future of computer vision–structural health monitoring.

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A newly developed, completely contactless structural health monitoring system framework based on the use of regular cameras and computer vision techniques is introduced for obtaining displacements and vibrations of structures, which are critical responses for performance-based design and evaluation of structures. To provide contactless and practical monitoring, the current vision-based displacement measurement methods are improved by eliminating the physical target attachment. This is achieved by means of utilizing imaging key-points as virtual targets. As a result, pixel-based displacements of a monitored structural location are determined by using an improved detection and match key-points algorithm, in which false matches are identified and discarded almost completely. To transform pixel-based displacements to engineering units, a practical camera calibration method is developed because calibration standard on a physical target no longer exists. Moreover, a framework for evaluating the accuracy of vision-based displacement measurements is established for the first time, which, in return, provides users with the most crucial information of a measurement. The proposed framework along with a conventional sensor network and a data acquisition system are applied and verified on a real-life stadium during football games for structural assessment. The results obtained by the new method are successfully validated with the data acquired from sensors such as linear variable differential transformers and accelerometers. Because the proposed method does not require any type of sensor and target attachment, common field works such as sensor installation, wiring, maintaining conventional data acquisition systems are not required. This advantage enables an inexpensive and practical way for structural assessment, especially for real-life structures.In the field of non-contact and wireless measurement systems for SHM, vision-based methods offer promising opportunities with their contactless and cost-effective deployment. Furthermore, advances in camera technologies as well as computer vision algorithms provide data and processed results that are comparable with the ones obtained by utilizing classical approaches (e.g., conventional sensors and visual methods). For example, some challenges related to surface damage of structures have been effectively solved by using image processing, such as detection, and quantification of cracks and delamination of concrete [2-6] and pavement [7,8]. Regarding structural identification systems for decision making, some researchers proposed hybrid sensor-camera monitoring systems while utilizing cameras and computer vision techniques for obtaining traffic information inputs [9][10][11][12][13]. Vision-based displacement and vibration monitoring are possibly the most commonly sought after responses of structures that can be obtained wirelessly. An early research to determine displacements of a real-life structure was conducted on a cable-suspension bridge near Los Angeles, CA [14]. In this study...

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