TBPos: Dataset for Large-Scale Precision Visual Localization

Masud Fahim, Ilona Söchting, Luca Ferranti, Juho Kannala, Jani Boutellier*

*Tämän työn vastaava kirjoittaja

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference article in proceedingsScientificvertaisarvioitu

Abstrakti

Image based localization is a classical computer vision challenge, with several well-known datasets. Generally, datasets consist of a visual 3D database that captures the modeled scenery, as well as query images whose 3D pose is to be discovered. Usually the query images have been acquired with a camera that differs from the imaging hardware used to collect the 3D database; consequently, it is hard to acquire accurate ground truth poses between query images and the 3D database. As the accuracy of visual localization algorithms constantly improves, precise ground truth becomes increasingly important. This paper proposes TBPos, a novel large-scale visual dataset for image based positioning, which provides query images with fully accurate ground truth poses: both the database images and the query images have been derived from the same laser scanner data. In the experimental part of the paper, the proposed dataset is evaluated by means of an image-based localization pipeline.

AlkuperäiskieliEnglanti
OtsikkoImage Analysis - Proceedings of SCIA 2023
ToimittajatRikke Gade, Michael Felsberg, Joni-Kristian Kämäräinen
KustantajaSpringer
Sivut84-94
Sivumäärä11
ISBN (painettu)978-3-031-31434-6
DOI - pysyväislinkit
TilaJulkaistu - 2023
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaScandinavian Conference on Image Analysis - Levi, Kittilä, Suomi
Kesto: 18 huhtik. 202321 huhtik. 2023
Konferenssinumero: 23

Julkaisusarja

NimiLecture Notes in Computer Science
Vuosikerta13885 LNCS
ISSN (painettu)0302-9743
ISSN (elektroninen)1611-3349

Conference

ConferenceScandinavian Conference on Image Analysis
LyhennettäSCIA
Maa/AlueSuomi
KaupunkiKittilä
Ajanjakso18/04/202321/04/2023

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