scholarly journals GEOMETRY AND TEXTURE MEASURES FOR INTERACTIVE VIRTUALIZED REALITY INDOOR MODELER

2015 ◽  
Vol XL-4/W5 ◽  
pp. 43-48 ◽  
Author(s):  
K. Thangamania ◽  
R. Ichikari ◽  
T. Okuma ◽  
T. Ishikawa ◽  
T. Kurata
Keyword(s):  
Affine Transformation ◽  
Indoor Environment ◽  
Texture Mapping ◽  
Labor Cost ◽  
Single Image ◽  
Prototype Implementation ◽  
Affine Transform ◽  
Multiple View ◽  
Shape From Texture

This paper discusses the algorithm to detect the distorted textures in the virtualized reality indoor models and automatically generate the necessary 3D planes to hold the undistorted textures. Virtualized reality (VR) interactive indoor modeler, our previous contribution enables the user to interactively create their desired indoor VR model from a single 2D image. The interactive modeler uses the projective texture mapping for mapping the textures over the manually created 3D planes. If the user has not created the necessary 3D planes, then the texture that belong to various objects are projected to the available 3D planes, which leads to the presence of distorted textures. In this paper, those distorted textures are detected automatically by the suitable principles from the shape from texture research. The texture distortion features such as the slant, tilt and the curvature parameters are calculated from the 2D image by means of affine transformation measured between the neighboring texture patches within the single image. This kind of affine transform calculation from a single image is useful in the case of deficient multiple view images. The usage of superpixels in clustering the textures corresponding to different objects, reduces the modeling labor cost. A standby database also stores the repeated basic textures that are found in the indoor model, and provides texture choices for the distorted floor, wall and other regions. Finally, this paper documents the prototype implementation and experiments with the automatic 3D plane creation and distortion detection with the above mentioned principles in the virtualized reality indoor environment.

Improvements of Infrared Touch Screen Calibration Algorithm Based on Affine Transformation

2014 ◽  
Vol 716-717 ◽  
pp. 1341-1345
Author(s):  
Wen Ming Guo ◽  
Gang Wang
Keyword(s):  
Affine Transformation ◽  
Touch Screen ◽  
The Other ◽  
Pass Rate ◽  
Sample Point ◽  
Affine Transform ◽  
Calibration Algorithm ◽  
Windows 8

Because the affine transformation can realize the coordinate translation, rotation, scaling, it is applied to calibrate the touch screen. But,requirements for touch errors of Windows 8 is ±0.5mm,and the pass rate of sample point must reach 4%.Therefore, simply use the method of draw-point to collect the sample point has been unable to meet the requirement of accuracy. This paper tries to propose two improved calibration algorithm based on affine transform, one method use drawing lines instead of marking point, the other devides the screen into a plurality of areas to use multiple calibration. This two kind of methods can effectively improve the calibration precision.

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 Indoor Positioning Using PnP Problem on Mobile Phone Images

2020 ◽  
Author(s):  
Hana Kubíčková ◽  
Karel Jedlička ◽  
Radek Fiala ◽  
Daniel Beran
Keyword(s):  
Indoor Environment ◽  
Feature Detection ◽  
Indoor Localization ◽  
Indoor Positioning ◽  
Control Points ◽  
Single Image ◽  
Sift Algorithm ◽  
Building Management ◽  
Indoor Positioning System ◽  
Clear Solution

As people grow a custom to effortless outdoor navigation there is a rising demand for similar possibility indoors as well. Unfortunately, indoor localization, being one of the necessary requirements for navigation, continues to be problem without a clear solution. In this article we are proposing a method for an indoor positioning system using a single image. This is made possible using small preprocessed database of images with known control points as the only preprocessing needed. Using feature detection with SIFT algorithm we can look through the database and find image which is the most similar to the image taken by user. Pair of images is then used to find coordinates of database image using PnP problem. Furthermore, projection and essential matrices are determined allowing for the user image localization ~ determining the position of the user in indoor environment. Benefits of this approach lies in the single image being the only input from user and no requirements for new onsite infrastructure and thus enables a simpler realization for the building management.

A semi-automatic multiple view texture mapping for the surface model extracted by laser scanning

2008 ◽  
Author(s):  
Zhichao Zhang ◽  
Xianfeng Huang ◽  
Fan Zhang ◽  
Yongmin Chang ◽  
Deren Li
Keyword(s):  
Laser Scanning ◽  
Texture Mapping ◽  
Surface Model ◽  
Multiple View

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 Reconstruction of a Three-Dimensional Human Model from a Single Image

2021 ◽  
Vol 24 (3) ◽  
pp. 485-504
Author(s):  
Alexander Sergeevich Tarasov ◽  
Vlada Vladimirovna Kugurakova
Keyword(s):  
3D Reconstruction ◽  
Three Dimensional ◽  
Texture Mapping ◽  
Original Model ◽  
Human Model ◽  
Implicit Function ◽  
Original Image ◽  
Single Image ◽  
Single Pixel

This article focuses on improving the 3D reconstruction of a human model from a single pixel-aligned implicit function image presented by FaceBook Research. The drawbacks of the method are revealed, associated with limiting the quality of the original image, recommendations are presented to avoid its incorrect operation, and approaches to improve the original model are proposed, which increase the identity of the resulting model by 1.33 times. We also worked out the tactics of subsequent texture mapping and implementation of a set of animations.

scholarly journals A Model and Software System for Coordinated and Multiple Views in Exploratory Visualization

2003 ◽  
Vol 2 (4) ◽  
pp. 258-269 ◽  
Author(s):  
Nadia Boukhelifa ◽  
Peter J. Rodgers
Keyword(s):  
Abstract Objects ◽  
Software System ◽  
Multiple Views ◽  
Formal Approach ◽  
Prototype Implementation ◽  
Multiple View ◽  
Dataflow Model ◽  
Visualization Systems

This paper describes a model for expressing coordination in multiple view visualization systems. We present the model and describe a prototype implementation that illustrates the features of the model. Current visualization systems tend to have an informal and inconsistent approach to coordination. Our model takes a formal approach to describing widely used coordination concepts. The model is based on views sharing abstract objects such as the visualization parameters of the dataflow model. Additionaly, this paper describes how current coordinations in exploratory visualization work and how novel coordinations can be constructed using our model.

scholarly journals Affine Transformation for Landmark Based Registration Initializer in ITK

2011 ◽  
Author(s):  
Eun young Kim ◽  
Hans Johnson ◽  
Norman Williams
Keyword(s):  
Affine Transformation ◽  
Linear Equations ◽  
Affine Transform ◽  
Transformation Algorithm

This document describes an affine transformation algorithm as an additional feature for landmark based registration in ITK www.itk.org. The algorithm is based on the paper by Spath, H [1]. The author derives a set of linear equations from paired landmarks and generates an affine transform from them. The method implemented here gives more freedom in the choice of registration and/or initialization method in ITK. The submission describes ITK implementation of the algorithm.

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