Content-Based Filtering for Fast 3D Reconstruction from Unstructured Web-Based Image Data

2014 ◽  
pp. 91-101 ◽  
Author(s):  
Konstantinos Makantasis ◽  
Anastasios Doulamis ◽  
Nikolaos Doulamis ◽  
Marinos Ioannides ◽  
Nikolaos Matsatsinis
Keyword(s):  
3D Reconstruction ◽  
Image Data ◽  
Web Based ◽  
Content Based Filtering

Artificial intelligence-based automatic visual inspection system for built heritage

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lukman E. Mansuri ◽  
D.A. Patel
Keyword(s):  
Artificial Intelligence ◽  
Visual Inspection ◽  
Image Data ◽  
Inspection System ◽  
Data Set ◽  
Web Based ◽  
Content Type ◽  
Built Heritage ◽  
Automatic Visual Inspection ◽  
Inspection Systems

PurposeHeritage is the latent part of a sustainable built environment. Conservation and preservation of heritage is one of the United Nations' (UN) sustainable development goals. Many social and natural factors seriously threaten heritage structures by deteriorating and damaging the original. Therefore, regular visual inspection of heritage structures is necessary for their conservation and preservation. Conventional inspection practice relies on manual inspection, which takes more time and human resources. The inspection system seeks an innovative approach that should be cheaper, faster, safer and less prone to human error than manual inspection. Therefore, this study aims to develop an automatic system of visual inspection for the built heritage.Design/methodology/approachThe artificial intelligence-based automatic defect detection system is developed using the faster R-CNN (faster region-based convolutional neural network) model of object detection to build an automatic visual inspection system. From the English and Dutch cemeteries of Surat (India), images of heritage structures were captured by digital camera to prepare the image data set. This image data set was used for training, validation and testing to develop the automatic defect detection model. While validating this model, its optimum detection accuracy is recorded as 91.58% to detect three types of defects: “spalling,” “exposed bricks” and “cracks.”FindingsThis study develops the model of automatic web-based visual inspection systems for the heritage structures using the faster R-CNN. Then it demonstrates detection of defects of spalling, exposed bricks and cracks existing in the heritage structures. Comparison of conventional (manual) and developed automatic inspection systems reveals that the developed automatic system requires less time and staff. Therefore, the routine inspection can be faster, cheaper, safer and more accurate than the conventional inspection method.Practical implicationsThe study presented here can improve inspecting the built heritages by reducing inspection time and cost, eliminating chances of human errors and accidents and having accurate and consistent information. This study attempts to ensure the sustainability of the built heritage.Originality/valueFor ensuring the sustainability of built heritage, this study presents the artificial intelligence-based methodology for the development of an automatic visual inspection system. The automatic web-based visual inspection system for the built heritage has not been reported in previous studies so far.

scholarly journals Sistem Retensi dan Alih Image Rekam Medis Inaktif RS Khusus Kanker MRCCC Siloam Semanggi

2021 ◽  
Vol 6 (1) ◽  
pp. 139
Author(s):  
Sudjiran Sudjiran ◽  
Akbar Syahbanta Limbong
Keyword(s):  
Data Processing ◽  
Image Data ◽  
Patient Data ◽  
Retention Data ◽  
Data Retention ◽  
Web Based ◽  
Patient Medical Record ◽  
Hospital Employees ◽  
Retention System ◽  
A Company

Along with the development of technology, the speed of data processing is needed in order to compete with competitors. A company must have an advantage over other companies if it does not want to lose in the competition. MRCCC Siloam Semanggi is a company that provides health services for cancer patients. One of the transaction processes within the hospital is sensing data in the form of images of patient data. Image data processing activities at this hospital are not yet structured and require a database in order to assist in fast data processing. This study aims to create an image transfer system to transfer physical documents into digital documents. This system is useful for hospital employees to be able to find documents easily for certain purposes, the system is made web-based using XAMPP, using PHP language with MySQL database. The results of the analysis of research that has been done, there are problems that arise related to the retention system in hospital patient data. Retention data collection activities are usually carried out by sorting out patient medical record documents from those not recorded on a computer.

A Robust Feature Points Matching Algorithm in 3D Optical Measuring System

2011 ◽  
Vol 383-390 ◽  
pp. 5193-5199 ◽  
Author(s):  
Jian Ying Yuan ◽  
Xian Yong Liu ◽  
Zhi Qiang Qiu
Keyword(s):  
3D Reconstruction ◽  
Digital Camera ◽  
Image Data ◽  
Epipolar Geometry ◽  
Bundle Adjustment ◽  
Measuring System ◽  
Feature Points ◽  
3 Dimensional ◽  
Feature Points Matching ◽  
Optical Measuring

In optical measuring system with a handheld digital camera, image points matching is very important for 3-dimensional(3D) reconstruction. The traditional matching algorithms are usually based on epipolar geometry or multi-base lines. Mistaken matching points can not be eliminated by epipolar geometry and many matching points will be lost by multi-base lines. In this paper, a robust algorithm is presented to eliminate mistaken matching feature points in the process of 3D reconstruction from multiple images. The algorithm include three steps: (1) pre-matching the feature points using constraints of epipolar geometry and image topological structure firstly; (2) eliminating the mistaken matching points by the principle of triangulation in multi-images; (3) refining camera external parameters by bundle adjustment. After the external parameters of every image refined, repeat step (1) to step (3) until all the feature points been matched. Comparative experiments with real image data have shown that mistaken matching feature points can be effectively eliminated, and nearly no matching points have been lost, which have a better performance than traditonal matching algorithms do.

Goal-Based Framework for Multi-User Personalized Similarities in e-Learning Scenarios

2014 ◽  
Vol 4 (1) ◽  
pp. 1-14 ◽  
Author(s):  
M. Waseem Chughtai ◽  
Imran Ghani ◽  
Ali Selamat ◽  
Seung Ryul Jeong
Keyword(s):  
Collaborative Filtering ◽  
Cold Start ◽  
Traditional Education ◽  
Experimental Result ◽  
Personalized Recommendation ◽  
Web Based ◽  
Web Based Learning ◽  
E Learning ◽  
Learning Scenarios ◽  
Content Based Filtering

Web-based learning or e-Learning in contrast to traditional education systems offer a lot of benefits. This article presents the Goal-based Framework for providing personalized similarities between multi users profile preferences in formal e-Learning scenarios. It consists of two main approaches: content-based filtering and collaborative filtering. Because only traditional content-based filtering is not sufficient to generate the recommendations for new-users, therefore, the proposed work hybridized multi user's collaborative filtering functionalities with personalized content-based profile preferences filtering. The main purpose of this proposed work is to (a) overcome the user-based cold-start profile recommendations and (b) improve the recommendations accuracy for new-users in formal e-learning recommendation systems. The experimental has been done by using the famous ‘MovieLens' dataset with 15.86% density of the user-item matrix with respect to ratings, while the evaluation of experimental results have been performed with precision mean and recall mean to test the effectiveness of Goal-based personalized recommendation framework. The Experimental result Precision: 81.90% and Recall: 86.56% show that the proposed framework goals performed well for the improvement of user-based cold-start issue as well as for content-based profile recommendations, using multi users personalized collaborative similarities, in formal e-Learning scenarios effectively.

scholarly journals Deep Learning Segmentation and 3D Reconstruction of Road Markings Using Multiview Aerial Imagery

2019 ◽  
Vol 8 (1) ◽  
pp. 47 ◽  
Author(s):  
Franz Kurz ◽  
Seyed Azimi ◽  
Chun-Yu Sheu ◽  
Pablo d’Angelo
Keyword(s):  
3D Reconstruction ◽  
Autonomous Vehicles ◽  
Automatic Segmentation ◽  
Image Data ◽  
Autonomous Driving ◽  
Aerial Imagery ◽  
Aerial Images ◽  
Aerial Image ◽  
Matching Problem ◽  
Convolutional Network

The 3D information of road infrastructures is growing in importance with the development of autonomous driving. In this context, the exact 2D position of road markings as well as height information play an important role in, e.g., lane-accurate self-localization of autonomous vehicles. In this paper, the overall task is divided into an automatic segmentation followed by a refined 3D reconstruction. For the segmentation task, we applied a wavelet-enhanced fully convolutional network on multiview high-resolution aerial imagery. Based on the resulting 2D segments in the original images, we propose a successive workflow for the 3D reconstruction of road markings based on a least-squares line-fitting in multiview imagery. The 3D reconstruction exploits the line character of road markings with the aim to optimize the best 3D line location by minimizing the distance from its back projection to the detected 2D line in all the covering images. Results showed an improved IoU of the automatic road marking segmentation by exploiting the multiview character of the aerial images and a more accurate 3D reconstruction of the road surface compared to the semiglobal matching (SGM) algorithm. Further, the approach avoids the matching problem in non-textured image parts and is not limited to lines of finite length. In this paper, the approach is presented and validated on several aerial image data sets covering different scenarios like motorways and urban regions.

scholarly journals The Multi-Temporal Database of Planetary Image Data (MUTED): A web-based tool for studying dynamic Mars

2018 ◽  
Vol 159 ◽  
pp. 56-65 ◽  
Author(s):  
T. Heyer ◽  
H. Hiesinger ◽  
D. Reiss ◽  
G. Erkeling ◽  
H. Bernhardt ◽  
...  
Keyword(s):  
Image Data ◽  
Temporal Database ◽  
Web Based ◽  
Multi Temporal

Mobile Robot Navigation Utilizing the WEB Based Aerial Images Without Prior Teaching Run

2017 ◽  
Vol 29 (4) ◽  
pp. 697-705 ◽  
Author(s):  
Satoshi Muramatsu ◽  
Tetsuo Tomizawa ◽  
Shunsuke Kudoh ◽  
Takashi Suehiro ◽  
◽  
...  
Keyword(s):  
Image Data ◽  
Aerial Images ◽  
Mobile Robot Navigation ◽  
Aerial Image ◽  
Map Matching ◽  
Robot Localization ◽  
Web Based ◽  
Map Data ◽  
Component Map ◽  
Robot Position

In order to realize the work of goods conveyance etc. by robot, localization of robot position is fundamental technology component. Map matching methods is one of the localization technique. In map matching method, usually, to create the map data for localization, we have to operate the robot and measure the environment (teaching run). This operation requires a lot of time and work. In recent years, due to improved Internet services, aerial image data is easily obtained from Google Maps etc. Therefore, we utilize the aerial images as a map data to for mobile robots localization and navigation without teaching run. In this paper, we proposed the robot localization and navigation technique using aerial images. We verified the proposed technique by the localization and autonomous running experiment.

Web-based 3D Reconstruction Service

2006 ◽  
Vol 17 (6) ◽  
pp. 411-426 ◽  
Author(s):  
Maarten Vergauwen ◽  
Luc Van Gool
Keyword(s):  
3D Reconstruction ◽  
Web Based

Three-dimensional reconstruction based on images from spiral high-resolution computed tomography of the temporal bone: anatomy and clinical application

2005 ◽  
Vol 119 (9) ◽  
pp. 693-698 ◽  
Author(s):  
Beom-Cho Jun ◽  
Sun-Wha Song ◽  
Ju-Eun Cho ◽  
Chan-Soon Park ◽  
Dong-Hee Lee ◽  
...  
Keyword(s):  
Computed Tomography ◽  
High Resolution ◽  
3D Reconstruction ◽  
Temporal Bone ◽  
Three Dimensional ◽  
Image Data ◽  
Computer Assisted ◽  
Surface Rendering ◽  
High Resolution Computed Tomography

The aim of this study was to investigate the usefulness of a three-dimensional (3D) reconstruction of computed tomography (CT) images in determining the anatomy and topographic relationship between various important structures. Using 40 ears from 20 patients with various otological diseases, a 3D reconstruction based on the image data from spiral high-resolution CT was performed by segmentation, volume-rendering and surface-rendering algorithms on a personal computer. The 3D display of the middle and inner ear structures was demonstrated in detail. Computer-assisted measurements, many of which could not be easily measured in vivo, of the reconstructed structures provided accurate anatomic details that improved the surgeon’s understanding of spatial relationships. A 3D reconstruction of temporal bone CT might be useful for education and increasing understanding of the anatomical structures of the temporal bone. However, it will be necessary to confirm the correlation between the 3D reconstructed images and histological sections through a validation study.

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