Cardiovascular magnetic resonance (CMR) imaging is the gold standard for the noninvasive assessment of left-ventricular (LV) function. Prognostic value of deformation metrics extracted directly from regular cine CMR images has been shown by numerous studies in the clinical setting, but with some limitations to detect torsion of the myocardium. Tagged CMR introduces trackable features in the myocardium that allow for the assessment local myocardial deformation, including torsion; it is, however, limited in the quantification of radial strain, which is a decisive metric for assessing the contractility of the heart. In order to improve cine-only and tagged-only approaches, we propose to combine the advantages of both image types by fusing global shape motion obtained from cine images with the local deformation obtained from tagged images. To this end, tracking is first performed on cine images, and subsequently, the resulting motion is utilized to mask and track tagged data. Our implementation is based on a recent finite element-based motion tracking tool with mechanical regularization. Joint cine and tagged images registration performance is assessed based on deformation metrics including LV strain and twist using human and in-house porcine datasets. Results show that joint analysis of cine and 3DTAG images provides better quantification of LV strain and twist as either data source alone.