Detect Geographical Location by Multi-View Scene Matching
Chen Liu, Yuan Yuan, Ganchao Liu · 2020
With the help of satellite geographical information, we present an innovative framework for localizing precisely while handling the varying views and different sources. We construct a convolutional neural network named Attentive Siamese-like Net (ASN) which can extract the multi-view scene representation. On top of it, a database retrieval system is established to search the realistic geographic coordinates quickly and reliably. For handling a complicated scene, a mass of visual data is collected from google satellite image and Google Earth Software. Experiments are carried out on two datasets of different scales and geographical range, which shows the superiority and effectiveness of our method.