In recent years, many coastlines worldwide have retreated under the influence of storm surges and other extreme events, exacerbated by intensifying wave conditions in certain regions and seasons. Consequently, wave-dissipating units (e.g., tetrapods) have been widely deployed for coastal protection. In this paper, we propose a novel three-dimensional geometric method for extracting robust feature points from 3D point clouds to track tetrapod displacements and assess seawall safety. The model represents a tetrapod as four cylinders sharing a common center. By fitting this geometric model to the point cloud, we obtain parameters that allow us to derive multiple feature points—such as the intersections of conical surfaces—which can also be verified through alternative measurement techniques. These feature points serve as stable references for position comparison and displacement estimation. As this research is at an early stage, we have not yet collected field data from full-scale tetrapods. Instead, we conducted indoor experiments using a 3D depth camera (Microsoft Azure) in place of LiDAR, utilizing several high-fidelity resin tetrapod scale models (approximately 10 cm in height) as test subjects. The results demonstrate the feasibility of our method: when compared against total-station measurements, our approach yields highly accurate displacement estimates (averaging approximately 3 mm). This provides a solid foundation for the future deployment of 3D laser scanning in seawall monitoring.