Recent years have seen a significant increase in the use of optical techniques for structural health monitoring and structural dynamics as an alternative to traditional contact-based methods. Techniques such as three-dimensional digital image correlation (3D-DIC) and three-dimensional point tracking (3DPT) have been widely used to extract full line-of-sight displacements and deformations of structures by analyzing images acquired from synchronized stereo cameras. To provide the necessary contrast for the correlation algorithm to work, the application of recognizable high-contrast markers in the form of a stochastic speckle pattern or optical targets on the surface of the structure of interest is necessary. This requirement can quickly become an obstacle to the analysis of large-scale civil and mechanical engineering structures where access, and therefore the ability to apply speckled patterns or optical targets, is limited. This research aims at overcoming this limitation by identifying and tracking naturally occurring features on the surface of the structure of interest (e.g., oil spills, rust stains, printed letters, bolts). This is achieved by using a newly proposed Augmented Centroid-Based Detector (A-CBD) method to extract features from an object of interest and track their displacement in two synchronized images over time. In this paper, the performance of the A-CBD method is compared with traditional 3DPT measurements performed using optical targets by extracting the time and frequency domain response of a cantilever beam. The results of the laboratory tests performed show that the precision of the proposed A-CBD is comparable to traditional 3DPT, yielding Time Response Assurance Criterion (TRAC) values consistently above 98% for both in-plane and out-of-plane displacements.