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Active appearance model is a classical feature extraction method, this feature point localization method is established based on the parametric statistical model, and it is widely applied in the face recognition areas. The AAM algorithm is used to localize the feature point of human face, on the basis of this, an optimal method is used to improve AAM fitting performance. The fuzzy neural network (FNN)...
The accurate and efficient facial expression recognition method was researched in this paper. The active shape model (ASM) was a usual method of pattern recognition such as the facial features localization and facial expression recognition etc. In this paper, the support vector machine (SVM) was researched for the facial expression recognition, on the basis of the research SVM theory, thus a new and...
Gender as a soft biometric attribute has been extensively investigated in the domain of computer vision because of its numerous potential application areas. However, studies have shown that gender recognition performance can be hindered by improper alignment of facial images. As a result, previous experiments have adopted face alignment as an important stage in the recognition process, before performing...
Recently, robots have become important to facilitate in our life, for example, the home automation robot that can service humans for their activity routine at home. In this way, the interaction between a human and the robot also becomes the importance and helps the communication with each other that should be appropriate. Our proposed of this study is to develop the robot that can interact with the...
The extensive use of video surveillance along with advances in face recognition has ignited concerns about the privacy of the people identifiable in recorded documents. Prior research into face de-identification algorithms has successfully proposed k-anonymity methods that guarantee to thwart face recognition software. However, there has been little investigation into the preservation of the data...
Publicly captured surveillance videos and images serve as a rich source of biometric identifiers. Of these, the face is the one most frequently used for the identification of people. In order to protect a person's identity, whenever it is not absolutely required, the face should be de-identified. One of the problems that any naturalness-preserving face de-identification method should address is the...
Many techniques in the area of 3D face recognition rely on local descriptors to characterize the surface-shape information around points of interest (or keypoints) in the 3D images. Despite the fact that a lot of advancements have been made in the area of keypoint descriptors over the last years, the literature on 3D-face recognition for the most part still focuses on established descriptors, such...
Facial expression synthesizing is a process of generating new face shapes from a given face. The earlier work on synthesizing facial expressions used 2D images. Only recently, the work has moved to using 3D face shapes due to the availability and improvement of 3D scanner acquisition technology. This paper presents a work on synthesizing neutral facial expression or neutralizing facial expression...
This paper presents a 3D face reconstruction method from one side-view face images. In order to reconstruct 3D face, Structure from Motion (SfM) method, which has widely used to reconstruct 3D face, and bilateral symmetry of human face are used. In the experiments, the reconstructed 3D facial shape is quantitatively compared with the 3D facial shape obtained from a 3D scanner, and the results show...
In this paper, we propose an efficient method to reconstruct the 3D models of a human face from a single 2D face image robustness under a variety facial expressions using the Deformable Generic Elastic Model (D-GEM). We extended the Generic Elastic Model (GEM) approach and combined it with statistical information of the human face and deformed generic depth models by computing the distance around...
One of the major challenges encountered by face recognition lies in the difficulty of handling arbitrary poses variations. While different approaches have been developed for face recognition across pose variations, many methods either require manual landmark annotations or assume the face poses to be known. These constraints prevent many face recognition systems from working automatically. In this...
To tackle the problem of automatic recognition of human eyebrow, a novel approach for shape analysis based on frontal face images is proposed in this paper. First, eyebrow curves are acquired by fitting cubic splines based on landmark points. Next, we propose to use a modified functional curve procrustes distance to measure the similarities among the cubic splines, and finally a multidimensional scaling...
Hybrid face recognition methods combine holistic and feature based approaches with the aim of reaching a high level of efficiency and robustness. In this paper we propose a fully automatic algorithm for multimodal data consisting of 2D face images and their corresponding 3D scans. The algorithm is based on the extraction of simple image features using the Scale Invariant Feature Transform and the...
An automatic facial expression recognition method is proposed to effectively recognize facial expression without any region unrelated to facial region. Support Vector Machine (SVM) is applied to recognize facial expression by Gabor features extracting using Gabor wavelet transformation after separate facial region from images Based on Active Appearance Models (AAMs), which reduce influence of illumination...
This paper proposed a new method Based on curvature Based LBP feature to recognize 3D facial expression automatically. 3D facial expression images are described by means of four images which gray level are the value of curvature-Based descriptors (principal curvatures k1, k2, mean curvature, shape index) and then encoded by LBP. To efficiently optimize the performance, Chi-square distance is employed...
This paper explores techniques for automatically recognizing the sentiment of facial expressions in social photos, especially those of politicians in the context of elections. We first use the Active Shape Model (ASM) to extract facial feature points. Next, the shape model points from the ASM are normalized to a standard shape and then submitted to a trained AdaBoost classifier to recognize the sentiment...
In current 3D facial expression recognition system, feature extraction has always been a critical point. We focus on encoding feature by using curvature information. 3D facial expression images are described by means of four images which gray level are the value of curvature-based descriptors (principal curvatures k1, k2, mean curvature, shape index) and then encoded by LBP. SVM classifier is employed...
Facial makeup has the ability to alter the appearance of a person. Such an alteration can degrade the accuracy of automated face recognition systems, as well as that of meth-ods estimating age and beauty from faces. In this work, we design a method to automatically detect the presence of makeup in face images. The proposed algorithm extracts a feature vector that captures the shape, texture and color...
This paper presents results on the assessment of facial wrinkles as a soft biometrics. Recently, several micro features such as moles, scars, freckles, etc. have been used in addition to more common facial features for face recognition. The discriminative power of facial wrinkles has not been evaluated. In this paper we present results of our experiments on evaluating the discriminative power of wrinkles...
In this paper, a 3D surface representation defined around several reference points taken on the surface is introduced. Such representation is obtained from the superposition of a set of indexed levels of geodesic curves and radial lines. A sampling criterion through a generalized version of the Shannon theorem allows the determination of the minimum resolution of both curves that describes faithfully...
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