Image-based indoor place-finder using image to plane matching

Determining indoor location using image based methods has the promise to be fast and intuitive. Nonetheless, a practical implementation needs to operate without knowledge of true camera pose and focal length, and be discriminating enough to identify location from multiple indoor locations that appear similar.In this paper, we propose an accurate and efficient method based on matching established planes in an environment to a query images. This greatly reduces the necessary computation, and improves accuracy by enforcing geometry on local feature descriptors. Accuracy is further improved by computing matching score based on number of matching pixels rather than descriptors as commonly done. Using a database of over 2000 planes and over 120 query images, we show our algorithm maintains accuracy over 86% even for challenging environments with multiple similar locations, and outperforms a feature based method by 10 - 40%.