scholarly journals A Practical Approach for Identity-Embodied 3D Artistic Face Modeling

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Tanasai Sucontphunt
Keyword(s):  
Real Time ◽  
Gpu Acceleration ◽  
Human Face ◽  
Human Identity ◽  
Face Modeling ◽  
Novice User ◽  
Face Model ◽  
The Face ◽  
Core Idea ◽  
Cartoon Characters

This paper describes a practical technique for 3D artistic face modeling where a human identity can be inserted into a 3D artistic face. This approach can automatically extract the human identity from a 3D human face model and then transfer it to a 3D artistic face model in a controllable manner. Its core idea is to construct a face geometry space and a face texture space based on a precollected 3D face dataset. Then, these spaces are used to extract and blend the face models together based on their facial identities and styles. This approach can enable a novice user to interactively generate various artistic faces quickly using a slider control. Also, it can run in real-time on an off-the-shelf computer without GPU acceleration. This approach can be broadly used in various 3D artistic face modeling applications such as a rapid creation of a cartoon crowd with different cartoon characters.

Real Time Person Recognition and Attendance Marking Using Holistic Based Approach

2017 ◽  
Vol 7 (7) ◽  
pp. 302
Author(s):  
Reshma P ◽  
Muneer VK ◽  
Muhammed Ilyas P
Keyword(s):  
Face Recognition ◽  
Real Time ◽  
High Accuracy ◽  
Efficient Technique ◽  
Human Face ◽  
Traditional Methods ◽  
Person Recognition ◽  
The Face

Face recognition is a challenging task for the researches. It is very useful for personal verification and recognition and also it is very difficult to implement due to all different situation that a human face can be found. This system makes use of the face recognition approach for the computerized attendance marking of students or employees in the room environment without lectures intervention or the employee. This system is very efficient and requires very less maintenance compared to the traditional methods. Among existing methods PCA is the most efficient technique. In this project Holistic based approach is adapted. The system is implemented using MATLAB and provides high accuracy.

Real-Time Face Decorations of Enlarging Eyes and Whitening Skin in Video Based on Face Posture Estimation by Particle Filter

2013 ◽  
Vol 17 (3) ◽  
pp. 392-403
Author(s):  
Norikazu Ikoma ◽  
◽  
Gefan Zhang
Keyword(s):  
Particle Filter ◽  
Real Time ◽  
Human Face ◽  
Real Time Processing ◽  
Still Image ◽  
Time Processing ◽  
The Face ◽  
Posture Estimation ◽  
On Line ◽  
Regional Position

Decorations of face such as enlarging eyes, whitening skin, rendering face slim, and so on are commercially successful in amusement arcades especially in Japan for still image and off-line processing. This paper proposes to decorate human face in video on-line and in real-time processing. Face posture estimation using particle filter plays a key role to decorate the face by precisely determining position of the eyes as well as determining regional position of face. Our proposed method conducts two decorations, enlarging eyes and whitening skin, based on the estimation result of face posture. Real-time implementation of the proposed method has been demonstrated for real scenes of indoor situation.

scholarly journals An Investigation of the Use of Eigen Values in Human Face Modeling for Recognition Tasks

2019 ◽  
pp. 1-9
Author(s):  
Emad F. Khalaf
Keyword(s):  
Face Recognition ◽  
Probabilistic Neural Network ◽  
Moving Average ◽  
Experimental Methodology ◽  
Image Modeling ◽  
Human Face ◽  
Face Modeling ◽  
Moving Average Filter ◽  
The Face ◽  
Average Filter

The face image modeling by eigenvalues is not a new track in the literature. However, a much complete study is required to achieve a comprehensive investigation of the topic. In this research paper, an experimental methodology is conducted for studying the different alternatives of utilizing the eigenvalues for human face recognition. For a better universal investigation, three popular databases are tested; Orl_faces, extended Yale face_A, and extended Yale face_B datasets. The main objective of the study is to find the best choice of using eigenvalues (EV) in face recognition. The technique of the moving average filter (MAF) is combined with that of eigenvalues to enhance the results. Probabilistic neural network (PNN) is used for classification. Three methods of this concept were developed as follows: EV, EV with MAF, and MAF alone. The elapsed time was tested, where for moving average filter was distinctly smaller than the other two methods. For the Yaleface_B database, the eigenvalues method was superior for each of the three training/testing systems. The results were enhanced after using different filters instead of a direct moving average filter to make the proposed method the superior again. The study proved the possibility of using eigenvalues in conjunction with a suitable filter to get acceptable results for all types of image limitations. The concluded ideas elicited from the study spot the light on the usefulness of utilization of eigenvalues in the face recognition tasks.

The Art Portrait, the Pixel and the Gene: Micro Construction of Macro Representation

2005 ◽  
Vol 11 (4) ◽  
pp. 60-71 ◽  
Author(s):  
Steven McCarthy
Keyword(s):  
Genetic Code ◽  
Human Genome ◽  
Binary Code ◽  
Digital Images ◽  
Human Face ◽  
Human Identity ◽  
Artistic Representations ◽  
The Face ◽  
Cultural Constructions ◽  
Creative Inquiry

Digital images rely on the fineness of pixels to create an illusion of pictorial reality, with individual ‘picture elements’ sacrificing themselves in service of the overall image. The elemental binary code underlying digital pictures has its parallel in human genetic code: bits of information are stored in the DNA, itself consisting of binary chemical relationships. The nature of human identity - as translated by artistic representations of the face - is emerging from this intersection. The mapping of the human genome has had implications for socio-cultural constructions of identity, especially for race and hereditary characteristics. This paper examines three artists whose creative inquiry addresses the human face and its relationship to digitisation, identity and genetic code: painter Chuck Close, Photomosaics® software inventor Rob Silvers, and photographer Nancy Burson. Their varying imaging strategies all employ micro and macro relationships, yet each offers different models for representing human identity.

Decimation of human face model for real-time animation in intelligent multimedia systems

2009 ◽  
Vol 47 (1) ◽  
pp. 147-162 ◽  
Author(s):  
Soo-Kyun Kim ◽  
Syung-Og An ◽  
Min Hong ◽  
Doo-Soon Park ◽  
Shin-Jin Kang
Keyword(s):  
Real Time ◽  
Multimedia Systems ◽  
Human Face ◽  
Face Model ◽  
Intelligent Multimedia

Creating adaptive predictions for packaging-critical quality parameters using advanced analytics and machine learning

TAPPI Journal ◽  
2019 ◽  
Vol 18 (11) ◽  
pp. 679-689
Author(s):  
CYDNEY RECHTIN ◽  
CHITTA RANJAN ◽  
ANTHONY LEWIS ◽  
BETH ANN ZARKO
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Predictive Analytics ◽  
Paper Industry ◽  
Quality Parameters ◽  
Fast Change ◽  
The Face ◽  
Model Tuning ◽  
Reducing Costs ◽  
Time Critical

Packaging manufacturers are challenged to achieve consistent strength targets and maximize production while reducing costs through smarter fiber utilization, chemical optimization, energy reduction, and more. With innovative instrumentation readily accessible, mills are collecting vast amounts of data that provide them with ever increasing visibility into their processes. Turning this visibility into actionable insight is key to successfully exceeding customer expectations and reducing costs. Predictive analytics supported by machine learning can provide real-time quality measures that remain robust and accurate in the face of changing machine conditions. These adaptive quality “soft sensors” allow for more informed, on-the-fly process changes; fast change detection; and process control optimization without requiring periodic model tuning. The use of predictive modeling in the paper industry has increased in recent years; however, little attention has been given to packaging finished quality. The use of machine learning to maintain prediction relevancy under everchanging machine conditions is novel. In this paper, we demonstrate the process of establishing real-time, adaptive quality predictions in an industry focused on reel-to-reel quality control, and we discuss the value created through the availability and use of real-time critical quality.

Conventions and temporal differences in painted faces: A study of posture and color distribution

2020 ◽  
Vol 2020 (11) ◽  
pp. 267-1-267-8
Author(s):  
Mitchell J.P. van Zuijlen ◽  
Sylvia C. Pont ◽  
Maarten W.A. Wijntjes
Keyword(s):  
Scientific Community ◽  
Human Face ◽  
Art Galleries ◽  
Art Collections ◽  
Color Distribution ◽  
Scientific Domain ◽  
The Face ◽  
And Gender ◽  
Changes Over Time ◽  
Over Time

The human face is a popular motif in art and depictions of faces can be found throughout history in nearly every culture. Artists have mastered the depiction of faces after employing careful experimentation using the relatively limited means of paints and oils. Many of the results of these experimentations are now available to the scientific domain due to the digitization of large art collections. In this paper we study the depiction of the face throughout history. We used an automated facial detection network to detect a set of 11,659 faces in 15,534 predominately western artworks, from 6 international, digitized art galleries. We analyzed the pose and color of these faces and related those to changes over time and gender differences. We find a number of previously known conventions, such as the convention of depicting the left cheek for females and vice versa for males, as well as unknown conventions, such as the convention of females to be depicted looking slightly down. Our set of faces will be released to the scientific community for further study.

Real Time Gender and Age Prediction using Deep Learning Techniques

2020 ◽  
Vol 9 (6) ◽  
pp. 797-801
Keyword(s):  
Deep Learning ◽  
Face Recognition ◽  
Real Time ◽  
Vital Role ◽  
Learning Techniques ◽  
Gender And Age ◽  
The Face ◽  
And Gender ◽  
Gender Detection ◽  
Age Prediction

Face recognition plays a vital role in security purpose. In recent years, the researchers have focused on the pose illumination, face recognition, etc,. The traditional methods of face recognition focus on Open CV’s fisher faces which results in analyzing the face expressions and attributes. Deep learning method used in this proposed system is Convolutional Neural Network (CNN). Proposed work includes the following modules: [1] Face Detection [2] Gender Recognition [3] Age Prediction. Thus the results obtained from this work prove that real time age and gender detection using CNN provides better accuracy results compared to other existing approaches.

GPU Acceleration of Algorithm to Design Directional Volumetric Display for Real-time Processing

2019 ◽  
pp. 989
Author(s):  
Daiki Matsumoto ◽  
Ryuji Hirayama ◽  
Naoto Hoshikawa ◽  
Hirotaka Nakayama ◽  
Tomoyoshi Shimobaba ◽  
...  
Keyword(s):  
Real Time ◽  
Gpu Acceleration ◽  
Real Time Processing ◽  
Time Processing ◽  
Volumetric Display

A Fast and Layered Real Rendering Method for Human Face Model—D-BRDF

2019 ◽  
pp. 99-106
Author(s):  
Pengbo Zhou ◽  
Xiaotong Liu ◽  
Heng Wang ◽  
Xiaofeng Wang
Keyword(s):  
Human Face ◽  
Face Model
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