Zobrazeno 1 - 10
of 2 266
pro vyhledávání: '"feature descriptor"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 14965-14981 (2024)
Multimodal remote sensing images (MRSIs) have extensive nonlinear radiation differences, geometric distortions, and noise corruption, which bring challenges for registration. Existing feature matching methods usually use gradient or phase congruency
Externí odkaz:
https://doaj.org/article/aab258416fbc488ab773d9ede317f6bd
Autor:
Janos Mark Szalai-Gindl, Daniel Varga
Publikováno v:
IEEE Access, Vol 12, Pp 67325-67354 (2024)
3D local descriptors are essential for many computer vision-related tasks: point cloud registration, object recognition, etc. The first descriptors appeared decades ago, but new methods are still emerging today. To solve the above mentioned problems
Externí odkaz:
https://doaj.org/article/6423a53f32654f6595a083c1860b638d
Publikováno v:
Applied Sciences, Vol 14, Iss 20, p 9375 (2024)
This paper presents a robust point cloud registration method based on a multi-scale covariance matrix descriptor and an accurate transformation estimation. Compared with state-of-the-art feature descriptors, such as FPH, 3DSC, spin image, etc., our p
Externí odkaz:
https://doaj.org/article/1e58a7ec9f064f8593c81819da70226d
Publikováno v:
Applied Sciences, Vol 14, Iss 20, p 9414 (2024)
A variety of methods for 3D object recognition and registration based on a deep learning pipeline have recently emerged. Nonetheless, these methods require large amounts of data that are not easy to obtain, sometimes rendering them virtually useless
Externí odkaz:
https://doaj.org/article/fafaecca18494aea86737695a39b4800
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 130, Iss , Pp 103928- (2024)
Within this study, we present a pioneering cross-platform point cloud registration (PCR) framework aimed at the automated alignment of UAV and terrestrial forest LiDAR point clouds. This framework leverages canopy profile skyline (CPS) descriptors an
Externí odkaz:
https://doaj.org/article/278e200892114e5ab24a047475bced9d
Akademický článek
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Publikováno v:
Visual Computing for Industry, Biomedicine, and Art, Vol 6, Iss 1, Pp 1-22 (2023)
Abstract Obtaining a 3D feature description with high descriptiveness and robustness under complicated nuisances is a significant and challenging task in 3D feature matching. This paper proposes a novel feature description consisting of a stable loca
Externí odkaz:
https://doaj.org/article/91924a8699ca4163bdea66c9d8970a24
Autor:
Mingda Jin, Wei Shao
Publikováno v:
Aerospace, Vol 11, Iss 6, p 417 (2024)
Craters are regarded as significant navigation landmarks during the descent and landing process in small body exploration missions for their universality. Recognizing and matching craters is a crucial prerequisite for visual and LIDAR-based navigatio
Externí odkaz:
https://doaj.org/article/c84d0577a21b4d458003f0dfdf807f38
Publikováno v:
Sensors, Vol 24, Iss 11, p 3358 (2024)
Aircraft engine systems are composed of numerous pipelines. It is crucial to regularly inspect these pipelines to detect any damages or failures that could potentially lead to serious accidents. The inspection process typically involves capturing com
Externí odkaz:
https://doaj.org/article/f61c9c5fb3674cb2a26dd8cfc99de307
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 9515-9528 (2023)
Differences in sensor types, resolutions, and imaging conditions can lead to considerable spectral differences in heterogeneous optical remote sensing images and the similarity of scale-invariant feature transform (SIFT) or local self-similarities (L
Externí odkaz:
https://doaj.org/article/526b3b25db20471b997d7496545ea89a