Minimally invasive cardiac catheter ablation procedures for treatment of myocardial arrhythmias require effective visualization of the relevant heart anatomy and electrophysiology. In a typical ablation procedure, the visualization tools available to the cardiologist include fluoroscopy, ultrasound, and a coarse 3D model of cardiac anatomy and electrical activity. Recent advances in visualization techniques for cardiac ablation procedures have provided the capability to incorporate detailed, patient specific anatomical image data into the procedure. One of the main challenges, however, lies in registering tracked catheter points collected during the procedure to preoperative, patient specific data. While cardiac gating can help to compensate for motion throughout the cardiac cycle, respiratory motion still remains an issue. In a previous simulation study, we showed that piecewise linear registration performs better than global registration for this application. There are two main goals of the current work. First, we generate a ground truth dataset that can be used to evaluate the performance of registration techniques in the application of cardiac ablation procedures. Second, we use this dataset to compare the performance of global versus piecewise registration.