Accuracy of 3-D reconstruction with occlusions

A marker has to be seen by at least two cameras for its three-dimensional (3-D) reconstruction, and the accuracy can be improved with more cameras. However, a change in the set of cameras used in the reconstruction can alter the kinematics. The purpose of this study was to quantify the harmful effect of occlusions on two-dimensional (2-D) images and to make recommendations about the signal processing. A reference kinematics data set was collected for a three degree-of-freedom linkage with three cameras of a commercial motion analysis system without any occlusion on the 2-D images. In the 2-D images, some occlusions were artificially created based on trials of real cyclic motions. An interpolation of 2-D trajectories before the 3-D reconstruction and two filters (Savitsky-Golay and Butterworth filters) after reconstruction were successively applied to minimize the effect of the 2-D occlusions. The filter parameters were optimized by minimizing the root mean square error between the reference and the filtered data. The optimal parameters of the filters were marker dependent, whereas no filter was necessary after a 2-D interpolation. As the occlusions cause systematic error in the 3-D reconstruction, the interpolation of the 2-D trajectories is more appropriate than filtering the 3-D trajectories.