Object-based place recognition and loop closing with jigsaw puzzle image segmentation algorithm

In this paper we present a novel place recognition method. Instead of directly using large numbers of SIFT features as visual landmarks, we first use a jigsaw puzzle image segmentation algorithm to segment the input scene image into regions that may correspond to objects or parts of objects. Based on these image regions, we further detect a set of salient objects to represent a place and only those SIFT descriptors that were contained in these salient objects were kept in the database. We also designed a range-tree data structure to organize these salient objects to increase the matching efficiency. Experiments show that place recognition can be achieved accurately and efficiently with these salient objects.