Tung Khuc

TL;DR: In this paper, a 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.

TL;DR: In this paper, a non-target computer vision-based method for displacement and vibration measurement is proposed by exploring a new type of virtual markers instead of physical targets, where the key points of measurement positions obtained using a robust computer vision technique named scale invariant feature transform show a potential ability to take the place of classical targets.

TL;DR: A new structural identification framework along with a damage indicator, displacement unit influence surface, and damage indicator using computer vision–based measurements for bridge stability measurements are presented.

TL;DR: In this paper, a real-world implementation of a novel monitoring system in which video images and conventional sensor network data are simultaneously analyzed to detect possible damage on a movable bridge is presented.

TL;DR: An enhanced noncontact displacement measurement method that employed an unmanned aerial vehicle (UAV) and computer vision algorithms and was verified on an experiment with a small-sized steel tower, providing an initial confirmation of the approach’s promising potential.