scholarly journals Hybrid Facial Features with Application in Person Identification

2020 ◽  
Author(s):  
Boonchana Purahong ◽  
Vanvisa Chutchavong ◽  
Hisayuki Aoyama ◽  
Chuchart Pintavirooj
Keyword(s):  
Three Dimensional ◽  
Facial Feature ◽  
Geometric Transformation ◽  
Facial Features ◽  
Facial Image ◽  
Edge Image ◽  
A Value ◽  
Linear Transform ◽  
Direct Linear Transform ◽  
Facial Identification

This paper presents the hybrid facial feature with identification and verification based on facial images. A query facial image had been taken under different conditions of the facial image of the same person (as the query). The query facial image database was constructed. We have used the technique of three-dimensional (3D) Dlib facial landmarks using a direct linear transform technique. A set of absolute affine invariance had been constructed from a series of the 3D landmark quadruplets, which make the facial identification robust to affine geometric transformation. These 3D facial features serve as a coarse feature depending on each individual facial structure. The construct of the 2D detail features represents the edge facial image confined between the 2D Dlib landmarks. The similarity of the 2D feature is achieved by aligning the 2D query edge image against that of the reference edge image. The geometric transformation matrix is estimated from the 2D Dlib landmarks, where correspondence is well established. An identification/verification cost function using a combination of local 2D facial features and global 3D facial features is utilized to verify and identify a query facial image against a candidate facial image(s). The performance of the algorithm yielding an area of 99.97% perfect classification is represented as a value under the receiver operating characteristic (ROC) curve.  

Facial Feature Extraction Algorithm Based on Machine Dynamic Vision

2013 ◽  
Vol 380-384 ◽  
pp. 4052-4056
Author(s):  
Bo Li ◽  
Xiao Qin Gu ◽  
Man Huai Lu
Keyword(s):  
Feature Extraction ◽  
Three Dimensional ◽  
Facial Feature ◽  
Stereoscopic Vision ◽  
Facial Features ◽  
Target Feature ◽  
Feature Extraction Method ◽  
Facial Feature Extraction ◽  
Dynamic Vision ◽  
Vision Algorithm

In video image sequences, assume that face forms larger interference in athletic process and use traditional algorithm to extract facial features which may lead to target pixel blending and feature missing problems. Three-dimensional face reconstruction has poor authenticity and characteristic distortion. In order to solve this problem, this paper proposes an anti-interference three-dimensional motion face feature extraction method based on multiple target constraint stereoscopic vision algorithm. Extract different facial images target feature points from video sequence, accurately calculate characteristics deformation in the process of face movement by adopting deformation constraint analysis method, resist the interferences of characteristics loss, and then make use of stereo vision technology to extract three-dimensional facial features. The experimental results show that this algorithm can effectively improve three-dimensional facial feature extraction in motion state, and achieve satisfactory results.

Facial Feature Extraction for Emotion Classification using Fuzzy c-mean Clustering

2020 ◽  
Vol 13 ◽  
Author(s):  
Garima Sharma ◽  
Latika Singh ◽  
Sumanlata Gautam
Keyword(s):  
Good Accuracy ◽  
Facial Feature ◽  
Support Vector ◽  
Facial Features ◽  
Emotion Classification ◽  
Facial Image ◽  
Linear Discriminant ◽  
Facial Feature Extraction ◽  
Multiple Datasets ◽  
Result Show

: The study presents a fuzzy based approach to extract facial features for human emotion classification. The proposed system determines the dimensional attributes (l-attribute and w-attribute) of mouth region extracted from the facial image using viola-jones algortithm. The feature set was generated by applying the proposed approach on a total of 136 images from JAFFE, NimStim and MUG dataset for happy and neutral emotion classes.The classification models were constructed for classifying happy and neutral emotion classes by using linear discriminant analysis, random forest, support vector machine, deep learning and naïve’s bayesian classification techniques. The result show good accuracy of 70% for the grayscale JAFFE and NimStim databases and 95% for the coloured MUG databse. The study can be further extended by considering multiple emotion classes from multiple datasets under different illumination conditions.

Facial Composite System Using Real Facial Features

2014 ◽  
Vol 22 (35) ◽  
pp. 9-15
Author(s):  
Soňa Duchovičová ◽  
Barbora Zahradníková ◽  
Peter Schreiber
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Composite System ◽  
Facial Feature ◽  
Facial Features ◽  
Feature Points ◽  
Facial Image ◽  
Facial Expression Classification ◽  
Expression Classification ◽  
Facial Composite

Abstract Facial feature points identification plays an important role in many facial image applications, like face detection, face recognition, facial expression classification, etc. This paper describes the early stages of the research in the field of evolving a facial composite, primarily the main steps of face detection and facial features extraction. Technological issues are identified and possible strategies to solve some of the problems are proposed.

scholarly journals Facial Feature Model for a Portrait Video Stylization

Symmetry ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 442 ◽  
Author(s):  
Dongxue Liang ◽  
Kyoungju Park ◽  
Przemyslaw Krompiec
Keyword(s):  
Facial Feature ◽  
Feature Model ◽  
Facial Features ◽  
Outer Face ◽  
Flow Estimation ◽  
Photorealistic Rendering ◽  
Stroke Models ◽  
The Face ◽  
Face Contour ◽  
Human Faces

With the advent of the deep learning method, portrait video stylization has become more popular. In this paper, we present a robust method for automatically stylizing portrait videos that contain small human faces. By extending the Mask Regions with Convolutional Neural Network features (R-CNN) with a CNN branch which detects the contour landmarks of the face, we divided the input frame into three regions: the region of facial features, the region of the inner face surrounded by 36 face contour landmarks, and the region of the outer face. Besides keeping the facial features region as it is, we used two different stroke models to render the other two regions. During the non-photorealistic rendering (NPR) of the animation video, we combined the deformable strokes and optical flow estimation between adjacent frames to follow the underlying motion coherently. The experimental results demonstrated that our method could not only effectively reserve the small and distinct facial features, but also follow the underlying motion coherently.

HUMAN FACE RECOGNITION FROM A SINGLE FRONT VIEW

1992 ◽  
Vol 06 (04) ◽  
pp. 571-593 ◽  
Author(s):  
CHING-WEN CHEN ◽  
CHUNG-LIN HUANG
Keyword(s):  
Face Recognition ◽  
Active Contour Model ◽  
Facial Feature ◽  
Recognition System ◽  
Facial Features ◽  
Human Face Recognition ◽  
Front View ◽  
Deformable Template ◽  
Face Recognition System ◽  
Feature Values

This paper presents a face recognition system which can identify the unknown identity effectively using the front-view facial features. In front-view facial feature extractions, we can capture the contours of eyes and mouth by the deformable template model because of their analytically describable shapes. However, the shapes of eyebrows, nostrils and face are difficult to model using a deformable template. We extract them by using the active contour model (snake). After the contours of all facial features have been captured, we calculate effective feature values from these extracted contours and construct databases for unknown identities classification. In the database generation phase, 12 models are photographed, and feature vectors are calculated for each portrait. In the identification phase if any one of these 12 persons has his picture taken again, the system can recognize his identity.

AN EFFICIENT APPROACH FOR FACE DETECTION AND FACIAL FEATURE LOCATION USING PRUNE-AND-SEARCH TECHNIQUE

2004 ◽  
Vol 18 (06) ◽  
pp. 987-1005 ◽  
Author(s):  
CHIN-CHEN CHANG ◽  
YUAN-HUI YU
Keyword(s):  
Face Detection ◽  
Facial Feature ◽  
Facial Features ◽  
Base Line ◽  
Human Face ◽  
Feature Location ◽  
Search Technique ◽  
Efficient Approach ◽  
Human Face Detection ◽  
Geometric Knowledge

This paper proposes an efficient approach for human face detection and exact facial features location in a head-and-shoulder image. This method searches for the eye pair candidate as a base line by using the characteristic of the high intensity contrast between the iris and the sclera. To discover other facial features, the algorithm uses geometric knowledge of the human face based on the obtained eye pair candidate. The human face is finally verified with these unclosed facial features. Due to the merits of applying the Prune-and-Search and simple filtering techniques, we have shown that the proposed method indeed achieves very promising performance of face detection and facial feature location.

Bending of an Infinite Beam on an Elastic Foundation

1937 ◽  
Vol 4 (1) ◽  
pp. A1-A7 ◽  
Author(s):  
M. A. Biot
Keyword(s):  
Elastic Foundation ◽  
Poisson Ratio ◽  
Elementary Theory ◽  
Three Dimensional ◽  
Bending Moment ◽  
Two Dimensional ◽  
Concentrated Load ◽  
Elastic Continuum ◽  
Infinite Beam ◽  
A Value

Abstract The elementary theory of the bending of a beam on an elastic foundation is based on the assumption that the beam is resting on a continuously distributed set of springs the stiffness of which is defined by a “modulus of the foundation” k. Very seldom, however, does it happen that the foundation is actually constituted this way. Generally, the foundation is an elastic continuum characterized by two elastic constants, a modulus of elasticity E, and a Poisson ratio ν. The problem of the bending of a beam resting on such a foundation has been approached already by various authors. The author attempts to give in this paper a more exact solution of one aspect of this problem, i.e., the case of an infinite beam under a concentrated load. A notable difference exists between the results obtained from the assumptions of a two-dimensional foundation and of a three-dimensional foundation. Bending-moment and deflection curves for the two-dimensional case are shown in Figs. 4 and 5. A value of the modulus k is given for both cases by which the elementary theory can be used and leads to results which are fairly acceptable. These values depend on the stiffness of the beam and on the elasticity of the foundation.

scholarly journals Calculation of acoustic flow-rate measurements error with the help of Fermat’s principle

2018 ◽  
Vol 211 ◽  
pp. 04007
Author(s):  
Alexander Petrov ◽  
Semyon Shkundin
Keyword(s):  
Control Systems ◽  
Cross Section ◽  
Flow Rate ◽  
Three Dimensional ◽  
Air Flow Rate ◽  
Velocity Measurements ◽  
Three Dimensional Flow ◽  
Automatic Control Systems ◽  
A Value ◽  
Flow Changes

The establishment of dispatching and automatic control systems for mine ventilation is impossible without the availability of perfect air flow rate sensors. Existing anemometers (tachometer, heat) do not meet these requirements. The error of average in cross section velocity measurements with such sensors reaches 15-20, sometimes 30%. The reason - the speed measured at one point is interpreted as the average over the cross section. The reliability of the sensors is small, because they are exposed to the damaging effect of a dusty atmosphere. Stationary installed anemometers clutter cross section, which is not always allowed. Fermat’s variational principle is used for derivation of the formula for the time of propagation of a sonic signal between two set points A and B in a steady three-dimensional flow of a fluid or gas. It is shown that the fluid flow changes the time of signal reception by a value proportional to the flow rate independently of the velocity profile. The time difference in the reception of the signals from point B to point A and vice versa is proportional with a high accuracy to the flow rate. It is shown that the relative error of the formula does not exceed the square of the largest Mach number. This makes it possible to measure the flow rate of a fluid or gas with an arbitrary steady subsonic velocity field

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