scholarly journals Registration of a 3D Model on a Single Image in Wide Angle Augmented Reality

2000 ◽  
Vol 4 (2) ◽  
pp. 37-53
Author(s):  
Youngmin Lee ◽  
Kwangyun Wohn
Keyword(s):  
Augmented Reality ◽  
Camera Calibration ◽  
3D Model ◽  
Reference Object ◽  
Wide Angle ◽  
Single Image ◽  
Registration Method ◽  
Internal Parameters ◽  
Outdoor Scenes ◽  
Calibration Free

This paper presents a new design of a wide angle augmented reality (AR) system and an effective registration method using a single image. The AR system is designed to meet three requirements: (1) the field of view (FOV) of the AR system must be wide enough to view reference constructions in outdoor scenes; (2) the precise registration of virtual objects should be guaranteed at any position of the image; and (3) the registration should be valid after motion of the camera. We use camera calibration and calibration-free methodologies in our approach. The internal parameters of the camera are determined roughly by the camera calibration and how the distortion coefficient of the camera lens is refined. The external parameters are determined by the calibration-free approach. At least four coplanar points forming a projected parallelogram are needed to construct the affine coordinates that are used for the registration. The only presumed condition is that the user specifies some projected parallelogram lines of the reference object interactively. The experimental results demonstrate the display prototype of the wide angle AR system with the distorted images removed and registration of 3D virtual models in static and dynamic camera environments.

Using Single Image Parallelepipeds for Camera Calibration

2014 ◽  
Vol 496-500 ◽  
pp. 1869-1872
Author(s):  
Ye Tian ◽  
Zhen Wei Wang ◽  
Feng Chen
Keyword(s):  
Camera Calibration ◽  
Topological Structure ◽  
Geometric Constraints ◽  
Human Vision ◽  
Single Image ◽  
Paper Briefly ◽  
Self Calibration ◽  
Internal Parameters ◽  
Complicated Process ◽  
Real Objects

Human vision is generally regarded as a complicated process from feeling to consciousness. In other words, it refers to a projection form 3-D object to 2-D image, as well as a cognition of real objects according to 2-D image,The process that a real object is modeled through some images is called 3-D reconstruction. Presently, camera calibration attracts many researchers, and it includes the internal parameters and the external parameters, such as coordinate of main point, parameters of rotation and translation. Some researchers have pointed out that parallelepiped has a strict topological structure and geometric constraints. Therefore, it is suitable for the self-calibration of camera. This paper briefly explains parallelepiped methodsand tries to apply this method to deal with self-calibration. The experiments show that this method is flexible and available. image.

scholarly journals Fast 3D Rotation Estimation of Fruits Using Spheroid Models

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2232
Author(s):  
Antonio Albiol ◽  
Alberto Albiol ◽  
Carlos Sánchez de Merás
Keyword(s):  
Fruit Quality ◽  
3D Model ◽  
Geometric Model ◽  
Fruit Shape ◽  
Single Camera ◽  
Global Score ◽  
Topographic Map ◽  
Single Image ◽  
Large Effort ◽  
Fruit Surface

Automated fruit inspection using cameras involves the analysis of a collection of views of the same fruit obtained by rotating a fruit while it is transported. Conventionally, each view is analyzed independently. However, in order to get a global score of the fruit quality, it is necessary to match the defects between adjacent views to prevent counting them more than once and assert that the whole surface has been examined. To accomplish this goal, this paper estimates the 3D rotation undergone by the fruit using a single camera. A 3D model of the fruit geometry is needed to estimate the rotation. This paper proposes to model the fruit shape as a 3D spheroid. The spheroid size and pose in each view is estimated from the silhouettes of all views. Once the geometric model has been fitted, a single 3D rotation for each view transition is estimated. Once all rotations have been estimated, it is possible to use them to propagate defects to neighbor views or to even build a topographic map of the whole fruit surface, thus opening the possibility to analyze a single image (the map) instead of a collection of individual views. A large effort was made to make this method as fast as possible. Execution times are under 0.5 ms to estimate each 3D rotation on a standard I7 CPU using a single core.

3D Model Registration Based on Feature Extraction

2011 ◽  
Vol 299-300 ◽  
pp. 1091-1094 ◽  
Author(s):  
Jiang Zhu ◽  
Yuichi Takekuma ◽  
Tomohisa Tanaka ◽  
Yoshio Saito
Keyword(s):  
Feature Extraction ◽  
Point Cloud ◽  
3D Model ◽  
Point Cloud Data ◽  
Coordinate Systems ◽  
High Precision Measurement ◽  
Registration Method ◽  
Cloud Data ◽  
Cad System ◽  
Complicated Model

Currently, design and processing of complicated model are enabled by the progress of the CAD/CAM system. In shape measurement, high precision measurement is performed using CMM. In order to evaluate the machined part, the designed model made by CAD system the point cloud data provided by the measurement system are analyzed and compared. Usually, the designed CAD model and measured point cloud data are made in the different coordinate systems, it is necessary to register those models in the same coordinate system for evaluation. In this research, a 3D model registration method based on feature extraction and iterative closest point (ICP) algorithm is proposed. It could efficiently and accurately register two models in different coordinate systems, and effectively avoid the problem of localized solution.

scholarly journals MATCHING AERIAL IMAGES TO 3D BUILDING MODELS BASED ON CONTEXT-BASED GEOMETRIC HASHING

2016 ◽  
Vol III-1 ◽  
pp. 17-23 ◽  
Author(s):  
J. Jung ◽  
K. Bang ◽  
G. Sohn ◽  
C. Armenakis
Keyword(s):  
Feature Extraction ◽  
Texture Mapping ◽  
Least Square Method ◽  
Least Square ◽  
Aerial Images ◽  
Single Image ◽  
Registration Method ◽  
Geometric Hashing ◽  
Building Models ◽  
Corner Points

In this paper, a new model-to-image framework to automatically align a single airborne image with existing 3D building models using geometric hashing is proposed. As a prerequisite process for various applications such as data fusion, object tracking, change detection and texture mapping, the proposed registration method is used for determining accurate exterior orientation parameters (EOPs) of a single image. This model-to-image matching process consists of three steps: 1) feature extraction, 2) similarity measure and matching, and 3) adjustment of EOPs of a single image. For feature extraction, we proposed two types of matching cues, edged corner points representing the saliency of building corner points with associated edges and contextual relations among the edged corner points within an individual roof. These matching features are extracted from both 3D building and a single airborne image. A set of matched corners are found with given proximity measure through geometric hashing and optimal matches are then finally determined by maximizing the matching cost encoding contextual similarity between matching candidates. Final matched corners are used for adjusting EOPs of the single airborne image by the least square method based on co-linearity equations. The result shows that acceptable accuracy of single image's EOP can be achievable by the proposed registration approach as an alternative to labour-intensive manual registration process.

scholarly journals INITIAL EVALUATION OF THE POTENTIAL OF SMARTPHONE STEREO-VISION IN MUSEUM VISITS

2019 ◽  
Vol XLII-2/W11 ◽  
pp. 837-842
Author(s):  
A. Masiero ◽  
G. Tucci ◽  
A. Conti ◽  
L. Fiorini ◽  
A. Vettore
Keyword(s):  
Augmented Reality ◽  
Stereo Vision ◽  
3D Model ◽  
New Technologies ◽  
Recognition System ◽  
Neural Network Classifier ◽  
Visual Effects ◽  
Geometric Information ◽  
Traditional Use ◽  
Museum Visit

<p><strong>Abstract.</strong> The recent introduction of new technologies such as augmented reality, machine learning and the worldwide spread of mobile devices provided with imaging, navigation sensors and high computational power can be exploited in order to drammatically change the museum visit experience. Differently from the traditional use of museum docents or audio guides, the introduction of digital technologies already proved to be useful in order to improve the interest of the visitor thanks to the increased interaction and involvement, reached also by means of visual effects and animations. Actually, the availability of 3D representations, augmented reality and navigation abilities directly on the visitor’s device can lead to a personalized visit, enabling the visitor to have an experience tailored on his/her needs. In this framework, this paper aims at investigating the potentialities of smartphone stereo-vision to improve the geometric information about the artworks available on the visitor’s device. More specifically, in this work smartphone stereo-vision will used as a 3D model generation tool in a 3D artwork recognition system based on a neural network classifier.</p>

Augmented Reality Recognition Registration Method Based on Text Features

2020 ◽  
Vol 57 (2) ◽  
pp. 021502
Author(s):  
李雪婷 Li Xueting ◽  
党建武 Dang Jianwu ◽  
王阳萍 Wang Yangping ◽  
高凡一 Gao Fanyi
Keyword(s):  
Augmented Reality ◽  
Registration Method ◽  
Text Features
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