Hip joint centre (HJC) localization is used in several biomedical applications, such as movement analysis and computer-assisted orthopaedic surgery. The purpose of this study was to validate in vitro a new algorithm (MC-pivoting) for HJC computation and to compare its performances with the state-of-the-art (least square approach-LSA). The MC-pivoting algorithm iteratively searches for the 3D coordinates of the point belonging to the femoral bone that, during the circumduction of the femur around the hip joint (pivoting), runs the minimum length trajectory. The algorithm was initialized with a point distribution that can be considered close to a Monte Carlo simulation sampling all around the LSA estimate. The performances of the MC-pivoting algorithm, compared with LSA, were evaluated with tests on cadavers. Dynamic reference frames were applied on both the femur and the pelvis and were tracked by an optical localizer. Results proved the algorithm accuracy (1.7mm+/-1.6, 2.3-median value+/-quartiles), reliability (smaller upper quartiles of the errors distribution with respect to LSA) and robustness (reduction of the errors also in case of large pelvis displacements).