Structural displacement is an important quantity in Structural Health Monitoring (SHM), as it directly reflects the condition and safety of structures. Vision-based measurement methods have been widely studied in recent years, mainly because they allow non-contact sensing and can cover relatively large areas. When these methods are applied to Unmanned Aerial Vehicle (UAV) platforms, however, additional challenges arise. In practical operation, platform motion and attitude changes tend to introduce drift into the measurements, which can noticeably affect the final results. In this study, a displacement measurement approach that combines vision sensing with a laser reference is investigated for both UAV-based and fixed-camera scenarios. A laser source installed on the ground projects a reference spot onto the structural surface, placed close to a multi-circle target. This setup provides a stable reference point that is less affected by platform movement. The displacement is then estimated by tracking the relative motion between the target and the laser spot, instead of relying directly on absolute measurements. With this design, a large part of the motion caused by the platform can be separated, allowing the structural displacement to be expressed in a ground-based coordinate system. The implementation includes several practical steps, such as adaptively selecting regions of interest, performing basic image processing, refining feature locations at the subpixel level, and updating scale factors during operation. Experiments with both UAV and stationary camera setups show that conventional measurements are strongly affected by low-frequency drift, while the laser-referenced results remain relatively stable across different measurement points. According to the Root Mean Square (RMS) analysis, about 77%–95% of the drift caused by platform motion can be reduced under UAV conditions. These results indicate that the method can serve as a practical option for displacement monitoring in UAV-based vision applications.