GPU-accelerated Hierarchical Panoramic Image Feature Retrieval for Indoor Localization

Feng Hu

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arXiv · 2006.08861

GPU-accelerated Hierarchical Panoramic Image Feature Retrieval for Indoor Localization

Feng Hu

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Abstract

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.

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Feng Hu. 2020-06-16. GPU-accelerated Hierarchical Panoramic Image Feature Retrieval for Indoor Localization. https://arxiv.org/abs/2006.08861

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