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Training Semantic Descriptors for Image-Based Localization

2022-02-02 12:17:59
Ibrahim Cinaroglu, Yalin Bastanlar

Abstract

Vision based solutions for the localization of vehicles have become popular recently. We employ an image retrieval based visual localization approach. The database images are kept with GPS coordinates and the location of the retrieved database image serves as an approximate position of the query image. We show that localization can be performed via descriptors solely extracted from semantically segmented images. It is reliable especially when the environment is subjected to severe illumination and seasonal changes. Our experiments reveal that the localization performance of a semantic descriptor can increase up to the level of state-of-the-art RGB image based methods.

Abstract (translated)

URL

https://arxiv.org/abs/2202.01212

PDF

https://arxiv.org/pdf/2202.01212.pdf


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