Structural health monitoring of bridge infrastructure is conventionally carried out either through the acquisition of data from embedded sensor arrays or through systematic inspection and documentation of surface-observable changes on the structure. External deterioration, such as crack formation or load-induced structural deformations, is typically identified during these inspections. However, conventional visual inspections are often labor-intensive and costly. Automated, camera-based photogrammetric monitoring methods offer a promising alternative to reduce both effort and expense. For the specific task of detecting vertical deformations in a bridge superstructure, a tripod-stabilized mono camera setup can be utilized. This approach enables the derivation of vertical deformations by tracking the displacement of target points within a predefined measurement field over time.</p> <p>This study investigates the derivation of vertical deformations from image sequences. Using a representative test bridge as a case study, the characteristic vertical deformation response induced by the traversal of a loaded vehicle is analyzed and documented. A measurement point field was affixed to the bridge superstructure and continuously observed. From the acquired image sequences, continuous vertical displacements were successfully derived, with a mean vertical deflection of the bridge superstructure in the range of −1.71 mm to +0.72 mm. The mean measurement noise, averaged across all monitored test cycles, amounted to 0.01 mm. The results demonstrate that high-quality deformation data can be acquired in a cost-efficient manner using a consumer-grade camera in conjunction with a standardized measurement field, thereby offering a viable low-cost alternative to conventional structural monitoring instrumentation.