| Title: | Semantic Segmentation in the Task of Long-Term Visual Localization |
| Authors: | Bureš, Lukáš Müller, Luděk |
| Citation: | BUREŠ, L. MÜLLER, L. Semantic Segmentation in the Task of Long-Term Visual Localization. In 6th International Conference, ICR 2021, St. Petersburg, Russia, September 27–30, 2021, Proceedings. Cham: Springer, 2021. s. 27-39. ISBN: 978-3-030-87724-8 , ISSN: 0302-9743 |
| Issue Date: | 2021 |
| Publisher: | Springer |
| Document type: | konferenční příspěvek ConferenceObject |
| URI: | 2-s2.0-85116430820 http://hdl.handle.net/11025/47257 |
| ISBN: | 978-3-030-87724-8 |
| ISSN: | 0302-9743 |
| Keywords in different language: | Long-term visual localization;Semantic segmentation;SuperPoint;SuperGlue;HRNet-OCR |
| Abstract in different language: | In this paper, it is discussed the problem of long-term visual localization with a using of the Aachen Day-Night dataset. Our experiments confirmed that carefully fine-tuning parameters of the Hierarchical Localization method can lead to enhance the visual localization accuracy. Next, our experiments show that it is possible to find an image’s area that does not add any valuable information in long-term visual localization and can be removed without losing the localization accuracy. The approach of using the method of semantic segmentation for preprocessing helped to achieve comparable state-of-the-art results in the Aachen Day-Night dataset. |
| Rights: | Plný text je přístupný v rámci univerzity přihlášeným uživatelům. © Springer |
| Appears in Collections: | Konferenční příspěvky / Conference Papers (KKY) OBD |
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