Reducing the computational cost of shape matching with the distance set

摘要

The distance set is known to be a versatile local descriptor of shape. As this is simply a set of ordinary distances between sample points on a shape, it is easy to construct and use. More importantly, it remains invariant under many settings and deformations, unlike other typical descriptors. However, in shape matching with distance sets, there is a tradeoff between performance and computational feasibility. In this paper, we present a new descriptor by improving the choice and order of elements in the distance set. We show that our descriptor is more efficient for shape matching from the viewpoint of computer algorithms. Additionally, we demonstrate that, although our descriptor runs more quickly in practice, it is equivalent to the original distance set in terms of shape retrieval.