Robust place recognition by avoiding confusing features and fast geometric re-ranking

There are millions of mobile phone applications based on location. Using a photo to precisely locate users location is useful and necessary. However, real-time location recognition or retrieval system is a challenging problem due to the really big differences between the query and the dataset in scale, viewpoint and lighting, or the noise existed in the foreground or background etc. To address this problem, we design a place recognition system and a new famous buildings dataset with ground truth labels. By adding a fast geometric image matching procedure before using RANSAC and applying a relative camera orientation calculation algorithm to filter the dataset collected from the Internet, we can substantially improve the efficiency of spatial verification and recognition accuracy.