Parallel alignment of a large number of range images

This chapter describes a method for parallel alignment of multiple range images. There are problems of computational time and memory space in aligning a large number of range images simultaneously. We developed a parallel method to address the problems. Searching for corresponding points between two range images is time-consuming and requires considerable memory space when performed independently. However, this process can be preformed in parallel, with each corresponding pair of range images assigned to a node. Because the computation time is approximately proportional to the number of vertices, by assigning the pairs so that the number of vertices computed is equal on each node, the load on each node is effectively distributed. In order to reduce the amount of memory required on each node, a hypergraph that represents the correspondences of range images is created, and heuristic graph partitioning algorithms are applied to determine the optimal assignment of the pairs. Moreover, by rejecting redundant dependencies, it becomes possible to accelerate computation time and reduce the amount of memory required on each node. The method was tested on a 16-processor PC cluster, where it demonstrated high extendibility and improved performance.