This paper addresses the problem of creating a faster version of the general ICP approach by exploiting the biometrics application context. In a recognition scenario, gallery images are enrolled into the database ahead of time, which gives us the opportunity to build related information before the probe comes into the system. In this paper, we present a novel approach, called "Pre-computed Voxel Closest Neighbors," to reduce the computational time for shape matching. The approach shifts the heavy computation burden to the enrollment stage, which can be done offline. Experiments in 3D ear biometrics with 302 subjects demonstrate the effectiveness of the approach.