Zobrazeno 1 - 10
of 426
pro vyhledávání: '"Hoegner, A."'
Numerous navigation applications rely on data from global navigation satellite systems (GNSS), even though their accuracy is compromised in urban areas, posing a significant challenge, particularly for precise autonomous car localization. Extensive r
Externí odkaz:
http://arxiv.org/abs/2407.21432
Point clouds and high-resolution 3D data have become increasingly important in various fields, including surveying, construction, and virtual reality. However, simply having this data is not enough; to extract useful information, semantic labeling is
Externí odkaz:
http://arxiv.org/abs/2402.06531
In the reconstruction of fa\c{c}ade elements, the identification of specific object types remains challenging and is often circumvented by rectangularity assumptions or the use of bounding boxes. We propose a new approach for the reconstruction of 3D
Externí odkaz:
http://arxiv.org/abs/2402.06521
3D building models with facade details are playing an important role in many applications now. Classifying point clouds at facade-level is key to create such digital replicas of the real world. However, few studies have focused on such detailed class
Externí odkaz:
http://arxiv.org/abs/2402.06506
Although highly-detailed LoD3 building models reveal great potential in various applications, they have yet to be available. The primary challenges in creating such models concern not only automatic detection and reconstruction but also standard-cons
Externí odkaz:
http://arxiv.org/abs/2402.06288
Autor:
Wysocki, Olaf, Xia, Yan, Wysocki, Magdalena, Grilli, Eleonora, Hoegner, Ludwig, Cremers, Daniel, Stilla, Uwe
Reconstructing semantic 3D building models at the level of detail (LoD) 3 is a long-standing challenge. Unlike mesh-based models, they require watertight geometry and object-wise semantics at the fa\c{c}ade level. The principal challenge of such dema
Externí odkaz:
http://arxiv.org/abs/2305.06314
Publikováno v:
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-2/W1-2022
Point clouds are widely regarded as one of the best dataset types for urban mapping purposes. Hence, point cloud datasets are commonly investigated as benchmark types for various urban interpretation methods. Yet, few researchers have addressed the u
Externí odkaz:
http://arxiv.org/abs/2304.07140
Publikováno v:
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-4/W2-2022
Semantic 3D building models are widely available and used in numerous applications. Such 3D building models display rich semantics but no fa\c{c}ade openings, chiefly owing to their aerial acquisition techniques. Hence, refining models' fa\c{c}ades u
Externí odkaz:
http://arxiv.org/abs/2303.05998
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol X-4-W5-2024, Pp 55-62 (2024)
Numerous navigation applications rely on data from global navigation satellite systems (GNSS), even though their accuracy is compromised in urban areas, posing a significant challenge, particularly for precise autonomous car localization. Extensive r
Externí odkaz:
https://doaj.org/article/151745d6158f4b1d99025bb347c11458
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol X-4-W5-2024, Pp 163-169 (2024)
Autonomous vehicles must navigate independently in an outdoor environment using features or objects. However, some objects may be more or less suitable for localization due to their attributes. Therefore, this work investigates the suitability of lan
Externí odkaz:
https://doaj.org/article/d629ab4863204359b3dfe2cbde0fbd79