  Indoor localization has many applications, such as commercial Location Based
Services (LBS), robotic navigation, and assistive navigation for the blind.
This paper formulates the indoor localization problem into a multimedia
retrieving problem by modeling visual landmarks with a panoramic image feature,
and calculating a user's location via GPU- accelerated parallel retrieving
algorithm. To solve the scene similarity problem, we apply a multi-images based
retrieval strategy and a 2D aggregation method to estimate the final retrieval
location. Experiments on a campus building real data demonstrate real-time
responses (14fps) and robust localization.
