The goal of intrasurgical registration is to establish a common reference frame between presurgical and intrasurgical three-dimensional data sets that correspond to the same anatomy. This paper presents two novel techniques that have application to this problem, high-speed pose tracking and intrasurgical data selection. In the first part of this paper, we describe an approach for tracking the pose of arbitrarily shaped rigid objects at rates up to 10 Hz. Static accuracies on the order of 1 mm in translation and 1 degree in rotation have been achieved. We have demonstrated the technique on a human face using a high-speed VLSI range sensor; however, the technique is independent of the sensor used or the anatomy tracked. In the second part of this paper, we describe a general purpose approach for selecting near-optimal intrasurgical registration data. Because of the high costs of acquisition of intrasurgical data, our goal is to minimize the amount of data acquired while ensuring registration accuracy. We synthesize near-optimal intrasurgical data sets, based on an analysis of differential surface properties of presurgical data. We demonstrate, using data from a human femur, that discrete-point data sets selected using our method are superior to those selected by human experts in terms of the resulting pose-refinement accuracy.