Analysis of mixed reality cross-device global localization algorithms based on point cloud registration
نویسندگان
چکیده
Современные подходы локализации и построения карты для устройств дополненной (AR) смешанной (MR) реальности основаны на извлечении локальных признаков с камеры. Наряду этим современные устройства AR/MR позволяют строить трехмерную сетку окружающего пространства. Однако существующие методы не решают задачу глобальной совместной из-за применения разных дескрипторов вычисления изображений. Используя карту пространства из трехмерной сетки, мы можем решить проблему AR/MR. Этот подход зависит от типа функций алгоритмов картографирования, используемых борту Сетку можно свести к облаку точек, которое состоит только вершин сетки. Мы предлагаем использованием облаков которые зависят устройства. проанализировали различные алгоритмы регистрации точек обсудили их ограничения задачи в помещении.
منابع مشابه
On the Effectiveness of Feature-based Lidar Point Cloud Registration
LIDAR systems have been regarded as novel technologies for efficiently acquiring 3-D geo-spatial information, resulting in broad applications in engineering and management fields. Registration of LIDAR point clouds of consecutive scans or different platforms is a prerequisite for fully exploiting advantages of afore-mentioned applications. In this study, the authors integrate point, line and pl...
متن کاملA Review of Point Cloud Registration Algorithms for Mobile Robotics
The topic of this review is geometric registration in robotics. Registration algorithms associate sets of data into a common coordinate system. They have been used extensively in object reconstruction, inspection, medical application, and localization of mobile robotics. We focus on mobile robotics applications in which point clouds are to be registered. While the underlying principle of those ...
متن کاملMultiple View Point Cloud Registration Based on 3D Lines
A point cloud registration method based on 3D lines extraction from 3D data to register point cloud with obvious edges is proposed in this paper. Firstly, the line feature point cloud (LFPC), which is corresponding to the objects' edges, is extracted from the measured 3D data by using surface curvature as a measure. Then, through applying the 3D Hough transformation on LFPC, the line directions...
متن کاملChallenging data sets for point cloud registration algorithms
The number of registration solutions in the literature has bloomed recently. The iterative closest point, for example, could be considered as the backbone of many laser-based localization and mapping systems. Although they are widely used, it is a common challenge to compare registration solutions on a fair base. The main limitation is to overcome the lack of accurate ground truth in current da...
متن کامل2.5D Multi-View Gait Recognition Based on Point Cloud Registration
This paper presents a method for modeling a 2.5-dimensional (2.5D) human body and extracting the gait features for identifying the human subject. To achieve view-invariant gait recognition, a multi-view synthesizing method based on point cloud registration (MVSM) to generate multi-view training galleries is proposed. The concept of a density and curvature-based Color Gait Curvature Image is int...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Komp?ûternye issledovaniâ i modelirovanie
سال: 2023
ISSN: ['2076-7633', '2077-6853']
DOI: https://doi.org/10.20537/2076-7633-2023-15-3-657-674