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Current deep learning methods have achieved human-level performance on Labeled Faces in the Wild (LFW) database, but we think it is because that the limited number of pairs on LFW do not capture the real difficulty of large-scale unconstrained face verification problem. Besides the intra-class variations like pose, illumination, occlusion and expression, highly visually similarity of different persons'...
In this paper, we present a large-scale database consisting of low cost Kinect 3D face videos, namely Lock3DFace, for 3D face analysis, particularly for 3D Face Recognition (FR). To the best of our knowledge, Lock3DFace is currently the largest low cost 3D face database for public academic use. The 3D samples are highly noisy and contain a diversity of variations in expression, pose, occlusion, time...
Face spoofing detection (i.e. face anti-spoofing) is emerging as a new research area and has already attracted a good number of works during the past five years. This paper addresses for the first time the key problem of the variation in the input image quality and resolution in face anti-spoofing. In contrast to most existing works aiming at extracting multiscale descriptors from the original face...
Most of existing visual quality assessment algorithms are tested on standard databases that are created in controlled viewing conditions (e.g. display device, viewing distance and lighting). This implies that all the recoded subjective scores are only valid for the specific settings used in the database. However, with the prevalence of mobile devices, the practical viewing environments can significantly...
Accuracy and speed of face recognition frameworks are two foremost concerns for practical applications in recent researches. Linear regression classification (LRC) is a very famous and powerful approach for face recognition; however, it cannot perform very well under occlusion situations. In this paper, the regression parameters of the module-LRC are analyzed when a query facial image is partially...
The traffic accidents is one of the important problems in our lives. The majority of traffic accidents are caused by inattentive or fatigue which is mostly related to drowsiness. An embedded and contactless system should be designed to deal with this problem in real world conditions. PERCLOS, is the most effective method for drowsiness detection, analyzes drowsiness level of the driver by using eye...
The paper presents a concept of Building Management System (based on SCADA/HMI system) for buildings with large scale automation system. The concept foundation is to build a control system database as an extension of Building Information Modelling (BIM) database, which contains definition of automation system and technological infrastructure controlled by the automation. Second foundation of the concept...
In the absence of lighting, due to the difference in the modality, it is very difficult to match the visible face database with the face images obtained in the thermal wavelength. Applying photometric preprocessing to reduce the modality difference, increases the face recognition performance from thermal to visible. In this study, different photometric preprocessing methods that can be used for face...
Recently, many people have begun to take pictures of meals and food either at home or in restaurants. These pictures are then uploaded to social networking services (SNS) where they are shared with friends. People want to take pictures of food that looks delicious, but they often find this difficult. This is because most people lack the knowledge required to take attractive pictures. There are many...
In any image, illumination is one of the challenges task and effect the performance of the system. In this paper, we have proposed new preprocessing approach to eliminate illumination effect from the human face images. In our approach we first apply Log transform on the input image to enhance illumination effect, output of this is given as input to the DoG filtering technique to smooth the image and...
We present a framework to automatically detect and remove shadows in real world scenes from a single image. Previous works on shadow detection put a lot of effort in designing shadow variant and invariant hand-crafted features. In contrast, our framework automatically learns the most relevant features in a supervised manner using multiple convolutional deep neural networks (ConvNets). The features...
The current paper suggests an initial segmentation system, detection and grouping of visual information based on faces to facilitate the use, the handling and validation of the VIDTIMIT database. In order to implement this basis, two methods of pretreatment for each face are used. Then faces are detected with the Viola and Jones algorithm based on weak type descriptors Haar and grouped by new faces...
In this paper we propose a new powerful face recognition method to increase the performance of face recognition algorithms. In our idea we integrate two dissimilarity measures namely City-block and Mahalanobis Cosine distance. The experiments are performed on the ORL database and YALE database. The results indicate the interest of the proposed technique compared to others methods of literature.
One of the major challenges in face recognition is that related to the differences in orientation or pose, the variations of illumination, the facial expressions, the occlusions and aging. In this paper, we propose an efficient method for face recognition in an uncontrolled environment where we fuse Gabor wavelets and Local Binary Patterns (LBP) in the feature extraction phase. Then, we apply the...
This paper describes a novel biometric scenario, where a person is authenticated at an ATM, and has to be re-identified from a camera within a very short time period, under very challenging illumination and pose conditions, and using data from a single session. The application scenario is the automatic retraction of forgotten card or cash at an ATM, which happens frequently, and causes inconvenience...
Single face-image comparisons are extremely challenging, particularly in the context of pose, expression variations and scene illumination changes. Most of the existing schemes are sub-space learning based, where dominant eigen-directions are determined from the covariance matrix computed over the entire face space. In this paper we propose a simple hashing method based on the relative magnitudes...
Estimating eye centers is an important computer vision problem with several applications. In the past, eye center localization was constrained by the use of special hardware such as infrared cameras. Methods that estimate eye centers based on visible light have also been suggested in the literature, but these methods are inaccurate when used with low resolution images and wide ranges of lighting....
This paper provides a comprehensive survey on the recent techniques of human activity recognition. The goal of the activity recognition is to automatically analyze the ongoing events. The applications of activity recognition are manifold, ranging from visual surveillance to control and video retrieval. The task is challenging due to variations in recording settings of people, environment and scene...
Digital retinal photography and the application of computer vision in ophthalmology are increasingly becoming helpful in the diagnosis and management of retinopathies and cardiovascular diseases. Although several automatic methods of detecting vessels in retinal images have been proposed, there has however been a need for improved automatic vessel detection methods that is capable of handling the...
This paper delivers a new database of iris images collected in visible light using a mobile phone's camera and presents results of experiments involving existing commercial and open-source iris recognition methods, namely: Iri-Core, VeriEye, MIRLIN and OSIRIS. Several important observations are made. First, we manage to show that after simple preprocessing, such images offer good visibility of iris...
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