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Wyszukujesz frazę "3D point reconstruction" wg kryterium: Temat


Wyświetlanie 1-3 z 3
Tytuł:
LEDs based video camera pose estimation
Autorzy:
Sudars, K.
Cacurs, R.
Homjakovs, I.
Judvaitis, J.
Powiązania:
https://bibliotekanauki.pl/articles/200249.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
camera pose estimation
image keypoint detection and matching
3D point reconstruction
object localization and tracking
oszacowanie ustawienia kamery
rekonstrukcja modelu 3D
lokalizacja obiektu
śledzenie obiektu
Opis:
For 3D object localization and tracking with multiple cameras the camera poses have to be known within a high precision. The paper evaluates camera pose estimation via a fundamental matrix and via the known object in environment of multiple static cameras. A special feature point extraction technique based on LED (Light Emitting Diodes) point detection and matching has been developed for this purpose. LED point detection has been solved searching local maximums in images and LED point matching has been solved involving patterned time functions for each light source. Emitting LEDs have been used as sources of known reference points instead of typically used feature point extractors like ORB, SIFT, SURF etc. In such a way the robustness of pose estimation has been obtained. Camera pose estimation is significant for object localization using the networks with multiple cameras which are going to an play increasingly important role in modern Smart Cities environments.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2015, 63, 4; 897-905
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multibeam data processing for 3D object shape reconstruction
Autorzy:
Kulawiak, M.
Łubniewski, Z.
Powiązania:
https://bibliotekanauki.pl/articles/332626.pdf
Data publikacji:
2017
Wydawca:
Polskie Towarzystwo Akustyczne
Tematy:
multibeam sonar
3D reconstruction
point cloud
wrecks
rasterization
Opis:
The technology of hydroacoustic scanning offers an efficient and widely-used source of geospatial information regarding underwater environments, providing measurement data which usually have the structure of irregular groups of points known as point clouds. Since this data model has known disadvantages, a different form of representation based on representing surfaces with simple geometric structures, such as edges and facets, is preferred for data featuring seabed surface relief and various underwater objects. In this paper, the authors propose a multiple-step approach to three-dimensional surface reconstruction from multibeam sonar measurements, relying on the proper application of various algorithms for noise reduction, data rasterization and classification. The results obtained by combining several different surface reconstruction algorithms with the proposed data processing technique were tested, and the strengths and weaknesses of each method were highlighted.
Źródło:
Hydroacoustics; 2017, 20; 105-112
1642-1817
Pojawia się w:
Hydroacoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Methods for quality improvement of multibeam and LiDAR point cloud data in the context of 3D surface reconstruction
Autorzy:
Kulawiak, M.
Łubniewski, Z.
Powiązania:
https://bibliotekanauki.pl/articles/332451.pdf
Data publikacji:
2016
Wydawca:
Polskie Towarzystwo Akustyczne
Tematy:
multibeam sonar
LiDAR
3D
point cloud
shape reconstruction
noise reduction
Opis:
Point cloud dataset is the transitional data model used in several marine and land remote-sensing applications. During further steps of processing, the transformation of point cloud spatial data to more complex models containing higher order geometric structures like edges and facets may be possible, if an appropriate quality level of input data is provided. Point cloud datasets usually contain a considerable amount of undesirable irregularities, such as strong variability of local point density, missing data, overlapping points and noise caused by scattering characteristics of the environment. For these reasons, processing such data can be quite problematic, especially in the field of object detection and threedimensional surface reconstruction. This paper is focused on applying the proposed methods for reducing the mentioned irregularities from several datasets containing 3D point clouds acquired by multibeam sonars and LiDAR scanners. The article also presents the results obtained by each method, and discusses their advantages.
Źródło:
Hydroacoustics; 2016, 19; 251-258
1642-1817
Pojawia się w:
Hydroacoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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