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The study presented aims to design and develop a face recognition system. The system utilized Viola Jones Algorithm in detecting faces from a given image. Also the system used Artificial Neural Networks in recognizing faces detected from the input. Upon experimentation the system generated can recognize human faces with accuracy of 87.05%. The system performs at its best if the person is around 150cm...
Plastic surgery is becoming more and more commonplace today due to its increasing acceptance in society and its cost-affordability. This in turn has led to the need for developing highly accurate post-surgery face recognition techniques, a problem space which differs significantly from traditional face recognition. In this paper we first conduct a statistical study to show that facial plastic surgery...
This paper presents a simple and efficient design of a face recognition system, where feature extraction algorithm is employed based on the principle of spatial cross-correlation. In the feature extraction process, instead of processing the entire image at a time, only a pair of rows or columns of an image is considered which makes the algorithm very efficient and low-cost. Considering the cross-correlations...
Facial Expression analysis is an interesting and challenging problem and has applications in many areas such as human computer interaction and robotics. Deriving an effective facial representation from original face images is an important step for successful facial expression recognition. In this paper, we are evaluating 2DPCA and LBP+2DPCA for facial representation. The three stages of facial expression...
Verification of Family Relationship from facial images is a challenging problem in computer vision, and there are very few attempts on tackling this problem in the literature. We present a survey on how to verify family relation by a various metric learning method, probabilistic framework and several methods which can extract critical points on a face using both location and texture information such...
Unimodal biometric systems encounters variety of limitations such as noisy input data, universality of traits, inability to enroll, unacceptable error rates and spoofing. Multimodal biometric system aims to fuse output of multiple biometric classifiers to alleviate some of these limitations. This paper proposes a novel multibiometric system using two most used biometric traits fingerprint and iris...
This paper presents an evaluation of the state-of-the-art face recognition using 2D, 3D and multimdal imagery methods. The twofold motivations are: (i) to provide the insight studies of automatic face recognition of 2D and 3D face imagery methods and (ii) to critically review the exiting 2D and 3D face recognition methods. Research trends to date are summarized, and challenges confronting the development...
Emotion recognition plays vital role in Human Computer Interface. This paper focuses on facial expression to identify seven universal human emotions such as, happy, disgust, neutral, anger, sad, surprise and fear. This is carried out by trying to extract unique facial expression features among emotions using Principal Component Analysis with Singular Value Decomposition and Euclidean Distance Classifier...
Communicating by those suffering from motor neuron disease has always been an arduous task. A lot of research has been carried out in finding new methods to assist this section of the society in order for them to freely communicate with the outside world. Though several methodologies exist using electrooculography or video oculography, most methods involve complex algorithms which are slow, power...
Face detection is a technique of detecting any face from a set of images. Face can be detected on the basis of features of the face such as pose, height, width etc. Although there are various techniques implemented for the detection of faces such as face detection using neural networks, but the features extracted using neural network is not sufficient and has low accuracy. Hence in this paper an efficient...
For benefiting from incorporating the class information, partial least squares (PLS) and its two dimension version (2DPLS) have been widely employed in face recognition when extracting principal components. However, currently popular statistic methods, such as principal component analysis (PCA) and linear discriminant analysis (LDA), only learn holistic, not parts-based, representations which ignore...
Facial expression recognition (FER) is important for robots and computers to achieve natural interaction with human. Over the years, researchers have proposed different feature descriptors, implemented different classification methods, and carried out test experiments on different datasets in realizing an automatic FER system. While achieving good performance, the most efficient feature space and...
Sparse representation of signals has been recently applied for hyperspectral imagery classification. It relies on the assumption that a test pixel can be linearly and sparsely represented as a combination of all training samples. Although recent work reported in the literature has exploited the sparsity of hyperspectral images, its use in effective multiscale representation of hyperspectral imagery...
Recently, the development of automatic face annotation techniques in online social networks has become a promising research area for the purpose of management of the large numbers of photographs uploaded to social network platforms. In this paper, we construct the pyramid database for the current owner in the Pyramid Database Access Control module by effectively making use of various types of social...
The face recognition problem is made difficult by the great variability in head rotation and tilt, lighting intensity and angle, facial expression, aging, partial occlusion (e.g. Wearing Hats, scarves, glasses etc.), etc. In this paper multi scale technique Discrete Wavelet Transform is used for preprocessing. The complexity is reduced by reducing the size of the image to 1 by 4. Discrete Wavelet...
The development of fully automatic face annotation techniques in online social networks (OSNs) is currently very important for effective management and organization of the large numbers of personal photos shared on social network platforms. In this paper, we construct the personalized and adaptive Fused Face Recognition unit for each member, which uses the Adaboost algorithm to fuse several different...
With the explosion development of multimedia information on the Internet and online sharing community, social network and Community multimedia data have received plenty of attention. In order to analyze and mining the structure and characteristics of online network communities with their large number of multimedia data automatically, we look into community photos as an basic data source for community...
Iris and Periocular biometrics has proved its effectiveness in accurately verifying the subject of interest. Recent improvements in visible spectrum Iris and Periocular verification have further boosted its application to unconstrained scenarios. However existing visible Iris verification systems suffer from low quality samples because of the limited depth-of-field exhibited by the conventional Iris...
In 2010, National Institute of Standard and Technology (NIST) of the U.S. published “Report on the Evaluation of 2D Still-Image Face Recognition Algorithms (MBE 2010 Still Face).” The report mentions that there has been a remarkably huge improvement in the area of face recognition technology from the start of FERET (FacE REcognition Technology) program in 1993 up to 2010. While MBE 2010 Still Face...
The Local Binary Patterns (LBP) feature extraction method is a theoretically and computationally simple and efficient methodology for texture analysis. The LBP operator is used in many applications such as facial expression recognition and face recognition. The original LBP is based on hard thresholding the neighborhood of each pixel, which makes texture representation sensitive to noise. In addition,...
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