دورية أكاديمية
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3D object reconstruction: A comprehensive view-dependent dataset

التفاصيل البيبلوغرافية
العنوان: 3D object reconstruction: A comprehensive view-dependent dataset
المؤلفون: Rafał Staszak, Dominik Belter
المصدر: Data in Brief, Vol 55, Iss , Pp 110569- (2024)
بيانات النشر: Elsevier, 2024.
سنة النشر: 2024
المجموعة: LCC:Computer applications to medicine. Medical informatics
LCC:Science (General)
مصطلحات موضوعية: Robotics, RGB-D camera, Depth images, Single-view scene reconstruction, Scene segmentation, Grasping objects, Computer applications to medicine. Medical informatics, R858-859.7, Science (General), Q1-390
الوصف: The dataset contains RGB, depth, segmentation images of the scenes and information about the camera poses that can be used to create a full 3D model of the scene and develop methods that reconstruct objects from a single RGB-D camera view. Data were collected in the custom simulator that loads random graspable objects and random tables from the ShapeNet dataset. The graspable object is placed above the table in a random position. Then, the scene is simulated using the PhysX engine to make sure that the scene is physically plausible. The simulator captures images of the scene from a random pose and then takes the second image from the camera pose that is on the opposite side of the scene. The second subset was created using Kinect Azure and a set of real objects located on the ArUco board that was used to estimate the camera pose.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2352-3409
العلاقة: http://www.sciencedirect.com/science/article/pii/S2352340924005365Test; https://doaj.org/toc/2352-3409Test
DOI: 10.1016/j.dib.2024.110569
الوصول الحر: https://doaj.org/article/54b2861112f64dd8a3840f0edda32ec8Test
رقم الانضمام: edsdoj.54b2861112f64dd8a3840f0edda32ec8
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:23523409
DOI:10.1016/j.dib.2024.110569