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When using a set of generic head-related transfer functions (HRTFs) for spatial sound rendering, personalisation can be considered to minimise localisation errors. This typically involves tuning the characteristics of the HRTFs or a parametric model according to the listener's anthropometry. However, measuring anthropometric features directly remains a challenge in practical applications, and the...
Component Analysis (CA) comprises of statistical techniques that decompose signals into appropriate latent components, relevant to a task-at-hand (e.g., clustering, segmentation, classification). Recently, an explosion of research in CA has been witnessed, with several novel probabilistic models proposed (e.g., Probabilistic Principal CA, Probabilistic Linear Discriminant Analysis (PLDA), Probabilistic...
LBP-based color features have shown excellent performance for color face recognition tasks, such as Color LBP, CLBP and LCVBP. However, existing methods encode the inter-channel information on pairs of color channels by applying the same spatial structure as that used in the intra-channel encoding. This results in a very high dimensional feature vector yet ineffective in encoding inter-channel information...
The performance of local descriptors such as SIFT drops under severe illumination changes. In this paper, we propose a Discriminative and Contrast Invertible (DCI) local feature descriptor. In order to increase the discriminative ability of the descriptor under illumination changes, a Laplace gradient based histogram is proposed. Moreover, a robust contrast flipping estimate is proposed based on the...
In recent years, face recognition has become a popular topic in academia and industry. Current local methods such as the local binary pattern (LBP), and scale invariant feature transform (SIFT) perform better than holistic methods, but their high complexity levels limit their application. In addition, SIFT-based schemes are sensitive to illumination variation. We propose an LBP edge-mapped descriptor...
We propose a Low-Dimensional Deep Feature based Face Alignment (LDFFA) method to address the problem of face alignment “in-the-wild”. Recently, Deep Bottleneck Features (DBF) has been proposed as an effective channel to represent input with compact, low-dimensional descriptors. The locations of fiducial landmarks of human faces could be effectively represented using low dimensional features due to...
The sparse representation based classification (SRC) performs not very well for small sample data. A discriminative common vector dictionary based SRC is introduced in this paper to address this issue. The contribution of this paper is that the dictionary of the proposed method is constructed by the discriminative common vector per class. The common vector represents the invariant property of each...
Cross-domain matching is a challenging problem with several applications like face recognition across pose and resolution, heterogeneous face recognition, etc. Coupled dictionary learning has emerged as a powerful technique for addressing such problems. A novel approach based on aligning two orthogonal dictionaries constructed independently from the two domains is proposed in this work. Once the dictionaries...
Ear recognition Is still a standing problem In biometrics and has become an open research area in recent years. In this paper, we explore a new local feature extraction technique pyramid histogram of oriented gradients (PHOG) to represent ear images. However, the PHOG descriptor of the ear image is significantly large. To reduce the dimension of the PHOG descriptor, linear discriminant analysis (LDA)...
This paper bring the decision about the problem facing by the visual impaired person. Here, We designed the device to system for the visually impaired person to handle problem in the environment. They face difficulties in independent accessing public transport since they cannot read the route number and unsure about the physical location of the bus, identifying the person, and also they find difficulty...
The goal of this project is to build an android based application for the mini-brain stroke victims to help them in detection and remediation of brain stroke. This application helps the user to recover from the after effects of the stroke which includes difficulties in speaking, upper limb movement and memory. The application also helps in the detection of brain stroke by automating the F.A.S.T technique...
A scientific discipline which includes methods that enable identification of people through their behavioral or physical characteristics or sometimes through both is known as Biometrics. Enhancement of security and the increase in its demand has paved way to an interest in an automated method of personal authentication which is based on Biometrics in recent times. Owing to the availability of multiple...
The impulse of ubiquitous biometrics may refer to the unique identification of an individual by analyzing psychological and behavioral traits. We have employed psychological biometric modalities such as AR database for face trait, poly-U database for palm trait and behavioral biometric modalities such as MCYT-100 database for signature trait, TIMIT database for speech trait. Desirable features extraction...
The proposed system aims to boost the performance of a face anti-spoofing system by fusing pulse based features with other spatial and temporal information that markedly define liveness. Most face recognition systems do not have an effective spoof detection module and hence are vulnerable to spoofing attacks. We address the above problem by developing a spatio-temporal mapping of face and then using...
Imaging using millimeter waves (mmWs) has many advantages including ability to penetrate obscurants such as clothes and polymers. Although conceal weapon detection has been the predominant mmW imaging application, in this paper, we aim to gain some insight about the potential of using mmW images for person recognition. We report experimental results using the mmW TNO database consisting of 50 individuals...
Presentation attacks (a.k.a, direct attacks or spoofing attacks) against face recognition systems have emerged as a serious security threat. To mitigate these attacks on conventional face recognition systems, several Presentation Attack Detection (PAD) algorithms have been developed, which address various Presentation Attack Instruments (PAI) including 3D face masks, 2D photo, wrap photo and electronic...
In the life of visually challenged people shopping is one of the greatest challenges. From getting around the supermarket to paying the bill at the cashier they need to rely on someone else. They never get a chance to shop on their own. Whether the person uses a cane, a seeing-eye dog or other sight tools, shopping is still a painstaking chore for them. This paper presents iShop — a complete mobile...
This paper discusses two important works. First work deals with extraction of key features from standard face databases. The data mined from the face databases consist of information related to number of facial images, male and female, different facial expressions, different poses, illumination conditions, facial image file format, synthetic faces, masked faces, infrared faces and number of subjects...
Sparse representation is a novel methodology that has off late received substantial attention for image classification and recognition. This paper presents a PCA-based dictionary building for sparse recognition. Recursive least square based auto-associative neural network model has been used for principal component extraction. Suggested network structure supports data compression along with principal...
The conventional method of taking attendance is done manually by the teacher or the administrator which requires considerable amount of time and efforts also involving errors and proxy attendance. As the number of students are increasing day by day, it is a challenging task for universities or colleges to monitor and maintain the record of the students. Automated systems involving use of biometrics...
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