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In our daily life we develop many activities that result imperceptible for the majority of us because the null effort that they represent to develop them, however, when we most develop those activities with any type of restriction, they acquire a higher level of difficulty. One simple activity is the communication process; we develop it in an easy way during almost all day, however, for people with...
Face sketch to digital image matching is an important challenge of face recognition that involves matching across different domains. Current research efforts have primarily focused on extracting domain invariant representations or learning a mapping from one domain to the other. In this research, we propose a novel transform learning based approach termed as DeepTransformer, which learns a transformation...
In order to enhance the classification accuracy of the two-dimensional feature of the image, the idea of a separate classification for each projection direction feature is proposed in this paper. Our method first divides the image into blocks and finds the two-dimensional sub-projection matrix of each sub-block, and then completes the feature extraction by using each column of the projection matrix...
We propose a new method in rank level fusion for biometric identification. Our method is based on the pool adjacent violators (PAV) algorithm after the ranks have been transformed to the approximated scores. We then show that our method outperforms various approaches that commonly used in biometric rank level fusion on NIST BSSR1 multimodal database.
Our aim is to use randomly generated image transformation in order to obtain image features of low dimensionality. The transformation consists of local projections of spatiallyorganized parts of an image, for example rectangular image blocks. After this transformation the content of an image is hidden and will not be stably recoverable, so it can be used in systems where privacy-preserving property...
In the past few decades, automatic face recognition has been an important vision task. In this paper, we exploit the spatial relationships of facial local regions by using a novel deep network. In the proposed method, face is spatially scanned with spatial long short-term memory (LSTM) to encode the spatial correlation of facial regions. Moreover, with facial regions of various scales, the complementary...
Face recognition systems as a biometrie system for human identification and verification has indeed shown a lot of progress over the years, illustrated through the various applications it has been used for. These applications include Human Computer Interaction systems, law, terrorist attacks, health and multimedia indexing. Furthermore, the installation of face recognition systems in public and private...
This paper describes a project concerning human recognition based on athlete numbers and their face detection. In daily life many people are training and participating in marathons, competitions or do sports like soccer. For that they wear t-shirts with a serial number that denotes their identity. For that detection of athlete numbers makes peoples life easier by collecting the data faster and automatically...
Facial landmark is to be determined point by point of areas such as eyes, nose, mouth, eyebrows on the face. Facial recognition studies can be generally categorized into two categories, local and global. All of the faces are used in the global face recognition while the face domain is divided into subspaces in the local face recognition. In face recognition studies facial landmarks are used for facial...
This paper presents the new face verification algorithm based on deep convolutional neural network. The algorithm produces face feature vectors, distance between these vectors allows to determine whether images from the same class. Comparative experimental results are given for LFW test database and modern face recognition algorithms. ROC-curve and equal error rate are used to determine the accuracy...
Designing a biometrie system based solely on skin texture is of interest because the face is sometimes oeeluded by hair or artefacts in many real-world contexts. This work presents a novel framework for the assessment of skin-based biometric systems incorporating skin quality information. The quality or purity of the extracted skin region is automatically established using pixel colour models prior...
In the interest of recent accomplishments in the development of deep convolutional neural networks (CNNs) for face detection and recognition tasks, a new deep learning based face recognition attendance system is proposed in this paper. The entire process of developing a face recognition model is described in detail. This model is composed of several essential steps developed using today's most advanced...
This paper proposes an effective fusion scheme for extracting more discriminative information from bimodal biometrics at data, feature and decision levels. In all these three levels of fusion, information from both face andfingerprint image of a single subject are fused to effectively represent it in a more discriminative ways. For all these three approaches, a combination of wavelet and principal...
The human face is an important biometric quantity which can be used to access a user-based system. As human face images can easily be obtained via mobile cameras and social networks, user-based access systems should be robust against spoof face attacks. In other words, a reliable face-based access system can determine both the identity and the liveness of the input face. To this end, various feature-based...
Multimodal biometrie systems seek to alleviate some of the limitations of unimodal biometrie systems by combining multiple pieces of evidence of the same person in the deeision-making process. In this paper, a novel multimodal biometric identification system is proposed based on fusing the results obtained from both the face and the left and right irises using deep learning approaches. Firstly, the...
The system proposed in this paper is an innovative biometrie authentication platform for access control applications based face recognition. The vision system is based multisensor fusion combining catadioptric sensor (calibrated with a field of view of 360°) and a Pan Tilt Zoom camera (PTZ). It is able to detect and track moving objects with a high zoom level. The recognition process is based on detection...
This paper presents the evaluation of visual features for the proposed two eye detection method applied to thermal images. The use of two eye region is due to its distinctive pattern and to overcome the issue of blurred and noisy characteristic in the thermal image. Comparative performance analysis on three different features which includes Haar, Histogram of Oriented Gradients (HoG) and Local Binary...
The problem of recognizing and discriminating mixed emotions in multi view faces using a web camera is discussed in this paper. Based on the literature, there are mainly seven basic emotions that humans can express and understand. However, in some faces in databases, there are characteristics of two or more of this basic emotions. The two databases of BU3DFE and UPM3DFE were tested for mixed emotion...
Recognition of human emotions from the imaging templates is useful in a wide variety of human-computer interaction and intelligent systems applications. However, the automatic recognition of facial expressions using image template matching techniques suffer from the natural variability with facial features and recording conditions. In spite of the progress achieved in facial emotion recognition in...
In this paper, we have proposed a multimodal biometric verification system adopting the physiological traits-face and fingerprint. The system has been evaluated for robustness analysis imposing the Additive White Gaussian noise (AWGN) on clean data of the employed databases-AR facial database, PolyU High-resolution fingerprint database. The unimodal and multimodal (pre and post matching fusion strategies)...
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