Soft tissue characterization with the inverse finite element method (FEM) optimization algorithm plays an important role in developing a physical model for medical simulations. However, tissue characterization that takes into account comprehensive boundary conditions for large deformations remains a challenge due to computational complexities and a lack of experimental data. In this study, soft tissue experiments on porcine livers were performed to measure the surface deformation and force response of soft tissues resulting from indentation loading depending on various indentation depths and two different tip shapes. Measurements were carried out with a three-dimensional (3D) optical system and a force transducer. Using the surface deformation and force response results, we estimated the maximum radius of influence, which can be utilized to determine the minimal required soft tissue model size for the FEM simulation. Considering the influence of the boundary conditions, the model was designed and integrated into an inverse FEM optimization algorithm to estimate the model parameters. The mechanical behavior of large deformations was characterized with FE modeling via hyperelastic and linear viscoelastic models.