Improved Image Retrieval for Efficient Localization in Urban Areas Using Location Uncertainty Data
Accurate localization of mobile devices based on camera-acquired visual media information usually requires a search over a very large GPS-referenced image database. This paper proposes an efficient method for limiting the search space for image retrieval engine by extracting and leveraging additional media information about Estimated Positional Error (EPE) to address complexity and accuracy issues in the search, especially to be used for compensating GPS location inaccuracy in dense urban areas. To test our procedure we have created a database by acquiring Google Street View (GSV) images and set of query images along with their EPE tag for down town of Chicago. Experimental results demonstrate how our proposed method can improve performance just by utilizing a data that is available for mobile systems such as smart phones.