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Gender recognition from face images is a challenging problem with applications in various knowledge domains, such as biometrics, security and surveillance, human-computer interaction, among others. In this work, we propose and evaluate a novel method for gender recognition based on a geometric descriptor constructed from a pre-defined face shape model. The proposed approach, tested on four different...
A common practice in modern face recognition methods is to specifically align the face area based on the prior knowledge of human face structure before recognition feature extraction. The face alignment is usually implemented independently, causing difficulties in the designing of end-to-end face recognition models. We study the possibility of end-to-end face recognition through alignment learning...
The Multi-task Cascaded Convolutional Networks (MTCNN) has recently demonstrated impressive results on jointly face detection and alignment. By using the hard sample ming and training a model on FER2013 datasets, we exploit the inherent correlation between face detection and facial express-ion recognition, and report the results of facial expression recognition based on MTCNN.
The proposed system for automobile security is a face detection and recognition application that control the automobile to be operated or restricted. This system is established for all types of door locks and particularly for automobiles. By using this methodology, resulted a better quality product with respect to documentation standards, code optimization, user acceptance due to adequately efficient,...
Facial expression recognition, which many researchers have put much effort in, is an important portion of affective computing and artificial intelligence. However, human facial expressions change so subtly that recognition accuracy of most traditional approaches largely depend on feature extraction. Meanwhile, deep learning is a hot research topic in the field of machine learning recently, which intends...
The Eigenface method is a classic face recognition method. This article is based on the method of Eigen face to recognize the facial expression. The aim of this method is to recognize the facial expression stored in a database. It uses a set of single static image with different expression labels as the training database, projected the training image to subspaces. The similar face of the tested expression...
This paper proposes an effective end-to-end face detection and recognition framework based on deep convolutional neural networks for home service robots. We combine the state-of-the-art region proposal based deep detection network with the deep face embedding network into an end-to-end system, so that the detection and recognition networks can share the same deep convolutional layers, enabling significant...
This paper provides a brief insight of some famous and particularly important algorithms used for face detection. Face detection is a technology used by/ computer systems to detect faces in a given digital image. Automatic face detection is a very complex problem in image processing and many methods and algorithms have been proposed like Viola Jones, CNN (cascade neural networks), Eigenface etc. We...
In this paper, we suggested AdBoost algorithm for further improvising the performance of system. In the enhanced adaboost, the eigen vectors are computed for facial region & applied classification. In the process of classification, we opt for process of learning, training & testing. As observed from the result sessions in the previous paper [13] the outcomes from the reboost detection are...
Security system based on biometrics is becoming more popular everyday as a part of safety and security measurement against all kind of crimes. Among several kinds of biometric security systems, face recognition is one of the most popular one. It is one of the most accurate, mostly used recognition methods in modern world. In this paper, two most popular face recognition methods have been discussed...
A principal components analysis (PCA) algorithm is one of the most important algorithms that has been used for doing many tasks; for example, data dimension reduction, data compression such as image compression, pattern recognition such as face detection and recognition, and many other things. An improved principal components analysis (IPCA) algorithm is similar to the PCA algorithm except that it...
Face detection and face attribute recognition, as hot topics in the field of computer vision, have been well studied. However, over the years, face detection and attribute recognition are regarded as different tasks and designed separately, which ignores the fact that they both classify samples based on the knowledge of skin color, face outline and face components etc. In this paper, we describes...
To solve the problem of the decline in success rate of face recognition with the change of facial attitude, We analyze the relationship of contour between frontal face and side face based on Gaussian process regression and propose a method to process side face with horizontal angle from −45° to +45°. We experiment in Multi-Pie and FERET database and the result shows the method in this paper significantly...
Detecting eyes in images is fundamental for many computer vision applications including face detection, face recognition, and human-computer interaction. Most existing methods are designed and tested on datasets acquired under controlled lab settings (e.g., fixed scale, known poses, clean background, etc.), leaving their performance to be further examined on real-world, uncontrolled images, such as...
We present a baseline convolutional neural network (CNN) structure and image preprocessing methodology to improve facial expression recognition algorithm using CNN. To analyze the most efficient network structure, we investigated four network structures that are known to show good performance in facial expression recognition. Moreover, we also investigated the effect of input image preprocessing methods...
The rapid development of Internet of Things and the current capabilities of high performance embedded systems have made them more attractive for the replacement of human personnel in hazardous or tedious duties. One such application is for guarding certain areas, such as the entrance of a warehouse for example. The aim of this work is to design an autonomous embedded security system for surveillance...
Facial expressions are the most visual method to convey emotions. Facial expressions of a person at different instances are not same. Automatic recognition of facial expressions is important for natural human-machine interfaces. Although human recognize facial expressions without delay, however expression reorganization by computer is still a challenge. In this proposed method Log Gabor filter bank...
Person identification is a very important task for intelligent devices when communicating or interacting with humans. A potential problem in real applications is that the amount of enrollment data is insufficient. When multiple modalities are available, it is possible to re-train the system online by exploiting the conditional independence between the modalities and thus improving classification accuracy...
An improved face detection method is proposed on the basis of traditional adaboost algorithm. The training samples are not distinguished in the traditional face detection based on adaboost algorithm, which results in ignoring face samples in the process of training and the face feature information can't be fully shown. In addition, because face samples and non-face samples are treated equally, all...
Facial expression analysis and recognition have been researched since the 17'th century. The foundational studies on facial expressions, which have formed the basis of today's research, can be traced back to few centuries ago. Precisely, a detailed note on the various expressions and movements of head muscles was given in 1649 by John Bulwer(1). Another important milestone in the study of facial expressions...
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