scholarly journals Introducing the FIDENTIS 3D Face Database

2018 ◽  
Vol 81 (2) ◽  
pp. 202-223 ◽  
Author(s):  
Petra Urbanová ◽  
Zuzana Ferková ◽  
Marie Jandová ◽  
Mikoláš Jurda ◽  
Dominik Černý ◽  
...  
Keyword(s):  
Large Scale ◽  
Applied Research ◽  
Face Database ◽  
Web Based ◽  
3D Face ◽  
3D Data ◽  
Varied Composition ◽  
3D Scans ◽  
Research Domains ◽  
3D Face Database

Abstract Face databases have assumed an important role in a variety of clinical and applied research domains. However, the number of datasets accessible to the scientific community is limited and the knowledge of their existence may be concealed from a wider range of specialists. In the present paper we introduce a sizeable dataset of 3D facial scans - FIDENTIS 3D Face Database (F3D-FD or FIDENTIS Database), which is accompanied by basic demographic and descriptive data. The database is structured according to recorded subjects, and comprises single-scan entries as well as a smaller number of multiscan entries. The multi-scan entries vary in the time passed between recording sessions and in the devices employed to collect the 3D data. The total number of 2476 individuals puts our database within the category of large-scale databases. The 3D scans are accessible through a web-based interface at www. fidentis.cz. A licensed version of the database is available to interested parties upon signing a license agreement. Because of its varied composition, and low target-specificity the database has capacity to be of great assistance for the worldwide research community.

Building Large Scale 3D Face Database for Face Analysis

2007 ◽  
pp. 343-350 ◽  
Author(s):  
Yuxiao Hu ◽  
Zhenqiu Zhang ◽  
Xun Xu ◽  
Yun Fu ◽  
Thomas S. Huang
Keyword(s):  
Large Scale ◽  
Face Database ◽  
Face Analysis ◽  
3D Face ◽  
3D Face Database

3D Face Recognition Based on Regional Shape Maps

2018 ◽  
Vol 22 (1) ◽  
pp. 141-146 ◽  
Author(s):  
Xiaoni Wang ◽  
Keyword(s):  
Face Recognition ◽  
Recognition Performance ◽  
3D Face Recognition ◽  
Face Database ◽  
Registration Method ◽  
3D Face ◽  
Feature Vectors ◽  
Input Face ◽  
Point To Point ◽  
3D Face Database

This study proposes an iterative closest shape point (ICSP) registration method based on regional shape maps for 3D face recognition. A neutral expression image randomly selected from a face database is considered as the reference face. The point-to-point correspondences between the input face and the reference face are achieved by constructing the points’ regional shape maps. The distance between corresponding point pairs is then minimized by iterating through the correspondence findings and coordinate transformations. The vectors composed of the closest shape points obtained in the last iteration are regarded as the feature vectors of the input face. These 3D face feature vectors are finally used for both training and recognition using the Fisherface method. Experiments are conducted using the 3D face database maintained by the Chinese Academy of Science Institute of Automation (CASIA). The results show that the proposed method can effectively improve 3D face recognition performance.

Quasi-Facial Communication for Online Learning Using 3D Modeling Techniques

2010 ◽  
pp. 181-191
Author(s):  
Wang Yushun ◽  
Zhuang Yueting
Keyword(s):  
Online Learning ◽  
Reference Model ◽  
Texture Mapping ◽  
Feature Points ◽  
Face Database ◽  
3D Face ◽  
Distant Learning ◽  
Facial Modeling ◽  
The Individual ◽  
3D Face Database

Online interaction with 3D facial animation is an alternative way of face-to-face communication for distance education. 3D facial modeling is essential for virtual educational environments establishment. This article presents a novel 3D facial modeling solution that facilitates quasi-facial communication for online learning. Our algorithm builds 3D facial models from a single image, with support of a 3D face database. First from the image, we extract a set of feature points, which are then used to automatically estimate the head pose parameters using the 3D mean face in our database as a reference model. After the pose recovery, a similarity measurement function is proposed to locate the neighborhood for the given image in the 3D face database. The scope of neighborhood can be determined adaptively using our cross-validation algorithm. Furthermore, the individual 3D shape is synthesized by neighborhood interpolation. Texture mapping is achieved based on feature points. The experimental results show that our algorithm can robustly produce 3D facial models from images captured in various scenarios to enhance the lifelikeness in distant learning.

scholarly journals A Hierarchical 3D Data Rendering System Synchronized with HTML

2006 ◽  
Vol 5 (2) ◽  
pp. 67-72
Author(s):  
Yousuke Kimura ◽  
Tomohiro Mashita ◽  
Atsushi Nakazawa ◽  
Takashi Machida ◽  
Kiyoshi Kiyokawa ◽  
...  
Keyword(s):  
Large Scale ◽  
Frame Rate ◽  
Web Based ◽  
Geometric Data ◽  
Large Scale Data ◽  
3D Data ◽  
Interactive Frame ◽  
Encoding Method ◽  
Hierarchical Encoding ◽  
Scale Data

We propose a new rendering system for large-scale, 3D geometic data that can be used with web-based content man-agement systems (CMS). To achieve this, we employed a geometry hierarchical encoding method "QSplat" and implemented this in a Java and JOGL (Java bindings of OpenGL) environment. Users can view large-scale geometric data using conventional HTML browsers with a non-powerful CPU and low-speed networks. Further, this system is independent of the platforms. We add new functionalities so that users can easily understand the geometric data: Annotations and HTML Synchronization. Users can see the geometric data with the associated annotations that describe the names or the detailed explanations of the particular portions. The HTML Synchronization enables users to smoothly and interactively switch our rendering system and HTML contents. The experimental results show that our system performs an interactive frame rate even for a large-scale data whereas other systems cannot render them

Quasi-Facial Communication for Online Learning Using 3D Modeling Techniques

2010 ◽  
pp. 727-737
Author(s):  
Yushun Wang ◽  
Yueting Zhuang
Keyword(s):  
Online Learning ◽  
Reference Model ◽  
Texture Mapping ◽  
Feature Points ◽  
Face Database ◽  
3D Face ◽  
Distant Learning ◽  
Facial Modeling ◽  
The Individual ◽  
3D Face Database

Online interaction with 3D facial animation is an alternative way of face-to-face communication for distance education. 3D facial modeling is essential for virtual educational environments establishment. This article presents a novel 3D facial modeling solution that facilitates quasi-facialcommunication for online learning. Our algorithm builds 3D facial models from a single image, with support of a 3D face database. First from the image, we extract a set of feature points, which are then used to automatically estimate the head pose parameters using the 3D mean face in our database as a reference model. After the pose recovery, a similarity measurement function is proposed to locate the neighborhood for the given image in the 3D face database. The scope of neighborhood can be determined adaptivelyusing our cross-validation algorithm. Furthermore, the individual 3D shape is synthesized by neighborhood interpolation. Texture mapping is achieved based on feature points. The experimental results show that our algorithm can robustly produce 3D facial models from images captured in various scenarios to enhance the lifelikeness in distant learning.

Evol2Circos: A Web-Based Tool for Genome Synteny and Collinearity Analysis and its Visualization in Fishes

2020 ◽  
Vol 111 (5) ◽  
pp. 486-490
Author(s):  
Manmohan Pandey ◽  
Basdeo Kushwaha ◽  
Ravindra Kumar ◽  
Prachi Srivastava ◽  
Suman Saroj ◽  
...  
Keyword(s):  
Large Scale ◽  
Software Tool ◽  
Web Browser ◽  
Web Based ◽  
Specific Data ◽  
Sequencing Technologies ◽  
Assembly Algorithms ◽  
User Friendly ◽  
Research Domains ◽  
Generation Sequencing

Abstract The advent of high throughput next-generation sequencing technologies and improved assembly algorithms have resulted in the accumulation of voluminous genomic data in public domains. These technologies have opened up entries for large scale comparative genome studies, especially the identification of conserved syntenic blocks among species, facilitating studies of the evolutionary importance of the conservation and variation in genomic organization. Synteny construction and visualization require computational and bioinformatics skills to prepare input files for the synteny analysis pipeline. The syntenic information for fishes is still in a juvenile stage and is scattered among different research domains. Here, we present a web-based tool “Evol2Circos” to provide a user-friendly graphical user interface (GUI) to analyze user-specific data for synteny construction and visualization, and to facilitate the browsing of syntenic information of different fishes using the Circos, bar, dual, and dot plots. The information generated from the tool can also be used for further downstream analyses. Evol2Circos software tool is tested under Ubuntu Linux. The web-browser, source code, documentation, user manual, example dataset and scripts are available online at 203.190.147.148/evole2circos/

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