Image Retrieval Using Landmark Indexing for Indoor Navigation

Abstract

A novel approach is proposed for real-time retrieval of images from a large database of overlapping images of an indoor environment. The procedure extracts visual features from images using selected computer vision techniques, and processes the extracted features to create a reduced list of features annotated with the frame numbers they appear in. This method is named landmark indexing. Unlike some state-of-the-art approaches, the proposed method does not need to consider large image adjacency graphs because the overlap of the images in the map sufficiently increases information gain, and mapping of similar features to the same landmark reduces the search space to improve search efficiency. Empirical evidence from experiments on real datasets shows better performance and accuracy than other approaches. Experiments are further performed by integrating the image retrieval technique into a 3D real-time navigation system. This system is tested in several indoor environments and all experiments show highly accurate localization results.