  We present a novel approach to place recognition well-suited to environments
with many dynamic objects--objects that may or may not be present in an agent's
subsequent visits. By incorporating an object-detecting preprocessing step, our
approach yields high-quality place representations that incorporate object
information. Not only does this result in significantly improved place
recognition in dynamic environments, it also significantly reduces
memory/storage requirements, which may increase the effectiveness of mobile
agents with limited resources.
