A Reconfigurable 3D Engineering Shape Search System: Part II — Database Indexing, Retrieval, and Clustering

2003 ◽  
Author(s):  
Kuiyang Lou ◽  
Subramaniam Jayanti ◽  
Natraj Iyer ◽  
Yagnanarayanan Kalyanaraman ◽  
Sunil Prabhakar ◽  
...  
Keyword(s):  
Relevance Feedback ◽  
3D Model ◽  
Feature Vector ◽  
3D Models ◽  
Semantic Gap ◽  
Multidimensional Index ◽  
Search System ◽  
Feature Vectors ◽  
Database Indexing ◽  
Database Clustering

This paper introduces database and related techniques for a reconfigurable, intelligent 3D engineering shape search system, which retrieves similar 3D models based on their shape content. Feature vectors, which are numeric “fingerprints” of 3D models, and skeletal graphs, which are the “minimal representations of the shape content” of a 3D model, represent the shape content. The Euclidean distance of the feature vectors, as well as the distance between skeletal graphs, provides indirect measures of shape similarity between the 3D models. Critical database issues regarding 3D shape search systems are discussed: (a) database indexing, (b) semantic gap, (c) subjectivity of similarity, and (d) database clustering. An Rtree based multidimensional index is used to speed up the feature-vector based search operation, while a decision treebased approach is used for efficiently indexing/searching skeletal graphs. Interactions among users and the search system, such as relevance feedback and feature vector reconfiguration, are used to bridge the semantic gap and to customize the system for different users. Database clustering of the R-tree index is compared with that generated by a selforganizing map (SOM). Synthetic databases and real 3D model databases are employed to investigate the efficiency of the multidimensional index and the effectiveness of relevance feedback.

EFFICIENT CONTENT-BASED IMAGE RETRIEVAL USING FUZZY ORGANIZATION AND OPTIMAL RELEVANCE FEEDBACK

2003 ◽  
Vol 03 (01) ◽  
pp. 171-208 ◽  
Author(s):  
ANASTASIOS DOULAMIS ◽  
NIKOLAOS DOULAMIS ◽  
THEODORA VARVARIGOU
Keyword(s):  
Image Retrieval ◽  
Relevance Feedback ◽  
Visual Information ◽  
Information Needs ◽  
Cross Correlation ◽  
Feature Vector ◽  
Fuzzy Classification ◽  
Content Based Image Retrieval ◽  
Visual Content ◽  
Feature Vectors

The performance of a Content-Based Image Retrieval System (CBIR) depends on (a) the system's adaptability to the user's information needs, which permits different types of indexing and simultaneously reduces the subjectivity of human perception for the interpretation of the image visual content and (b) the efficient organization of the extracted descriptors, which represent the rich visual information. Both issues are addressed in this paper. Descriptor organization is performed using a fuzzy classification scheme fragmented into multidimensional classes, instead of the previous works where fuzzy histograms were created in one dimension using, for example, the feature vector norm. Multidimensionality relates the descriptors with one another and thus allows a compact and meaningful visual representation by mapping the elements of the resulted feature vectors with a physical visual interpretation. Furthermore, fuzzy classification is applied for all visual content descriptors, in contrast to the previous approaches where only color information is exploited. Two kinds of content descriptors are extracted in our case; global-based and region-based. The first refers to the global image characteristics, while the second exploits the region-based properties. Regions are obtained by applying a multiresolution implementation of the Recursive Shortest Spanning Tree (RSST) algorithm, called M-RSST in this paper. The second issue is addressed by proposing a computationally efficient relevance feedback mechanism based on an optimal weight updating strategy. The scheme relies on the cross-correlation measure, instead of the Euclidean distance which is mainly used in most relevance feedback algorithms. Cross-correlation is a normalized measure, which expresses how similar the two feature vectors are and thus it indicates a metric of their content similarity. The proposed scheme can be recursively implemented in the case of multiple feedback iterations, instead of the previous approaches. Furthermore, it provides reliable results regardless of the number of selected sample and the feature vector size improving relevance feedback performance, as compared to other approaches.

A 3D Engineering Model Retrieval Algorithm Based on Relevance Feedback and Features Combination

2013 ◽  
Vol 579-580 ◽  
pp. 340-344
Author(s):  
Ting Zhuang ◽  
Xu Tang Zhang ◽  
Zhen Xiu Hou
Keyword(s):  
Relevance Feedback ◽  
3D Model ◽  
3D Models ◽  
Semantic Knowledge ◽  
Retrieval Algorithm ◽  
Engineering Model ◽  
Feedback Information ◽  
Low Level ◽  
Model Retrieval ◽  
High Level

In order to reuse 3D models and design knowledge efficiently, a number of 3D model retrieval algorithms based on content features of models have been proposed in recent years. Although, the features-based methods have achieved some progress, there are two limitations stilly. The first, single content feature cant be suit for all kinds of 3D models; different features have different strengths and weakness. The second, semantic gap, the semantic of model is independent from low-level characteristics. For those two issues, we present a 3D engineering model retrieval algorithm based on relevance feedback and features combination in this paper. The proposed method takes advantage of multiple features by allying them with weights. In the retrieval process, our method utilizes the Particle Swarm Optimization to update the weights dynamically based on users relevance feedback information in order to narrowing the gap between high-level semantic knowledge and low-level content features. The Experiments, based on publicly available 3D model database Engineering Shape Benchmark (ESB) developed by Purdue University, suggested that the proposed approach has better retrieval ability than traditional ones.

The structure of the modules of the search system by geometric shape based on the repeated use of design knowledge

2021 ◽  
pp. 8-11
Author(s):  
Keyword(s):  
3D Model ◽  
Geometric Shape ◽  
Design Knowledge ◽  
Class Diagram ◽  
Geometric Form ◽  
Search System ◽  
Knowledge Component ◽  
Hu Moments ◽  
Repeated Use

The development of a diagram of the components of a search system by geometric form and a class diagram of obtaining design knowledge using Hu-moments is considered. Keywords: 3D model, PLM, Hu-moments, design knowledge, component diagram. [email protected]

scholarly journals UNDERWATER PHOTOGRAMMETRY DIGITAL SURFACE MODEL (DSM) OF THE SUBMERGED SITE OF THE ANCIENT LIGHTHOUSE NEAR QAITBAY FORT IN ALEXANDRIA, EGYPT

2019 ◽  
Vol XLII-2/W10 ◽  
pp. 1-8 ◽  
Author(s):  
M. Abdelaziz ◽  
M. Elsayed
Keyword(s):  
3D Model ◽  
Low Cost ◽  
Data Gathering ◽  
Archaeological Site ◽  
3D Models ◽  
Surface Model ◽  
Digital Surface Model ◽  
Architectural Elements ◽  
3D Photogrammetry ◽  
First Time

<p><strong>Abstract.</strong> Underwater photogrammetry in archaeology in Egypt is a completely new experience applied for the first time on the submerged archaeological site of the lighthouse of Alexandria situated on the eastern extremity of the ancient island of Pharos at the foot of Qaitbay Fort at a depth of 2 to 9 metres. In 2009/2010, the CEAlex launched a 3D photogrammetry data-gathering programme for the virtual reassembly of broken artefacts. In 2013 and the beginning of 2014, with the support of the Honor Frost Foundation, methods were developed and refined to acquire manual photographic data of the entire underwater site of Qaitbay using a DSLR camera, simple and low cost materials to obtain a digital surface model (DSM) of the submerged site of the lighthouse, and also to create 3D models of the objects themselves, such as statues, bases of statues and architectural elements. In this paper we present the methodology used for underwater data acquisition, data processing and modelling in order to generate a DSM of the submerged site of Alexandria’s ancient lighthouse. Until 2016, only about 7200&amp;thinsp;m<sup>2</sup> of the submerged site, which exceeds more than 13000&amp;thinsp;m<sup>2</sup>, was covered. One of our main objectives in this project is to georeference the site since this would allow for a very precise 3D model and for correcting the orientation of the site as regards the real-world space.</p>

scholarly journals FROM ARCHIVE DOCUMENTATION TO ONLINE 3D MODEL VISUALIZATION OF NO LONGER EXISTING STRUCTURES: THE TURIN 1911 PROJECT

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 837-844
Author(s):  
D. Einaudi ◽  
A. Spreafico ◽  
F. Chiabrando ◽  
C. Della Coletta
Keyword(s):  
Cultural Heritage ◽  
3D Model ◽  
3D Models ◽  
World's Fair ◽  
Existing Structures ◽  
Present Generation ◽  
Technical Issues ◽  
Digital Documentation ◽  
3D Documentation ◽  
Model Visualization

Abstract. Rebuilding the past of cultural heritage through digitization, archiving and visualization by means of digital technology is becoming an emerging issue to ensure the transmission of physical and digital documentation to future generations as evidence of culture, but also to enable present generation to enlarge, facilitate and cross relate data and information in new ways. In this global effort, the digital 3D documentation of no longer existing cultural heritage can be essential for the understanding of past events and nowadays, various digital techniques and tools are developing for multiple purposes.In the present research the entire workflow, starting from archive documentation collection and digitization to the 3D models metrically controlled creation and online sharing, is considered. The technical issues to obtain a detail 3D model are examined stressing limits and potentiality of 3D reconstruction of disappeared heritage and its visualization exploiting three complexes belonging to 1911 Turin World’s Fair.

scholarly journals VERIFICATION OF POTENCY OF AERIAL DIGITAL OBLIQUE CAMERAS FOR AERIAL PHOTOGRAMMETRY IN JAPAN

2016 ◽  
Vol XLI-B1 ◽  
pp. 63-68 ◽  
Author(s):  
Ryuji Nakada ◽  
Masanori Takigawa ◽  
Tomowo Ohga ◽  
Noritsuna Fujii
Keyword(s):  
3D Model ◽  
3D Models ◽  
Aerial Photographs ◽  
Digital Cameras ◽  
Digital Mapping ◽  
Aerial Photogrammetry ◽  
Public Survey ◽  
Survey Accuracy ◽  
Left And Right ◽  
Simultaneous Adjustment

Digital oblique aerial camera (hereinafter called “oblique cameras”) is an assembly of medium format digital cameras capable of shooting digital aerial photographs in five directions i.e. nadir view and oblique views (forward and backward, left and right views) simultaneously and it is used for shooting digital aerial photographs efficiently for generating 3D models in a wide area. &lt;br&gt;&lt;br&gt; For aerial photogrammetry of public survey in Japan, it is required to use large format cameras, like DMC and UltraCam series, to ensure aerial photogrammetric accuracy. &lt;br&gt;&lt;br&gt; Although oblique cameras are intended to generate 3D models, digital aerial photographs in 5 directions taken with them should not be limited to 3D model production but they may also be allowed for digital mapping and photomaps of required public survey accuracy in Japan. &lt;br&gt;&lt;br&gt; In order to verify the potency of using oblique cameras for aerial photogrammetry (simultaneous adjustment, digital mapping and photomaps), (1) a viewer was developed to interpret digital aerial photographs taken with oblique cameras, (2) digital aerial photographs were shot with an oblique camera owned by us, a Penta DigiCAM of IGI mbH, and (3) accuracy of 3D measurements was verified.

Low Cost Methods Used to Create 3D Models

2017 ◽  
Author(s):  
Agnieszka Chmurzynska ◽  
Karolina Hejbudzka ◽  
Andrzej Dumalski
Keyword(s):  
Laser Scanning ◽  
3D Model ◽  
Low Cost ◽  
3D Models ◽  
3D Modelling ◽  
Kinect Sensor ◽  
Applied Technology ◽  
Gaming Environment

During the last years the softwares and applications that can produce 3D models using low-cost methods have become very popular. What is more, they can be successfully competitive with the classical methods. The most wellknown and applied technology used to create 3D models has been laser scanning so far. However it is still expensive because of the price of the device and software. That is why the universality and accessibility of this method is very limited. Hence, the new low cost methods of obtaining the data needed to generate 3D models appeare on the market and creating 3D models have become much easier and accessible to a wider group of people. Because of their advantages they can be competitive with the laser scanning. One of the methods uses digital photos to create 3D models. Available software allows us to create a model and object geometry. Also very popular in the gaming environment device – Kinect Sensor can be successfully used as a different method to create 3D models. This article presents basic issues of 3D modelling and application of various devices, which are commonly used in our life and they can be used to generate a 3D model as well. Their results are compared with the model derived from the laser scanning. The acquired results with graphic presentations and possible ways of applications are also presented in this paper.

3D Model-Based Semantic Categorization of Still Image 2D Objects

2011 ◽  
Vol 2 (4) ◽  
pp. 19-37
Author(s):  
Raluca-Diana Petre ◽  
Titus Zaharia
Keyword(s):  
3D Model ◽  
3D Models ◽  
Multimedia Databases ◽  
Indexing Methods ◽  
Still Image ◽  
Shape Indexing ◽  
Indexing And Retrieval ◽  
Video Indexing And Retrieval ◽  
Matching Techniques ◽  
Image Object

Automatic classification and interpretation of objects present in 2D images is a key issue for various computer vision applications. In particular, when considering image/video, indexing, and retrieval applications, automatically labeling in a semantically pertinent manner/huge multimedia databases still remains a challenge. This paper examines the issue of still image object categorization. The objective is to associate semantic labels to the 2D objects present in natural images. The principle of the proposed approach consists of exploiting categorized 3D model repositories to identify unknown 2D objects, based on 2D/3D matching techniques. The authors use 2D/3D shape indexing methods, where 3D models are described through a set of 2D views. Experimental results, carried out on both MPEG-7 and Princeton 3D models databases, show recognition rates of up to 89.2%.

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