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Within the forensics community, there is a growing interest in automatic biometric-based approaches for describing subjects in an image. By labeling scars, marks and tattoos, a collection of these discriminative attributes can be assigned to images and used to assist in large-scale person search and identification. Typically, the imagery considered in a forensics context consists to some degree of...
The data captured by existing standoff biometric systems typically has lower biometric recognition performance than their close range counterparts due to imaging challenges, pose challenges, and other factors. To assist in overcoming these limitations systems typically perform in a multi-modal capacity such as Honeywell's Combined Face and Iris (CFAIRS) [21] system. While this improves the systems...
Registration is a very important step in object recognition. Accurate detection of the eye centers, eye corners, mouth and nose are critical for face recognition and more broadly, for face processing. In this work, we have evaluated three techniques, namely AAM, Stacked ASM and CLM, for automatic detection of landmarks under the problem of extremely dense registration scheme for the face. Further...
In this paper, we propose a novel approach using Kernel Class-dependent Feature Analysis (KCFA) combined with facial color based features to tackle the problem of ethnicity classification on large scale face databases. In our approach, a new design of multiple filtered responses of the Kernel Class-dependent Feature Analysis is used for ethnicity classes. In order to improve the robustness of our...
Sparse representation has gained much attention of many researchers recently due to the powerful ability of representing and compressing the original sample. The sparse based classification (SRC) method has been proposed for face recognition and applied to many other fields, which method aims to sparse represent test sample on training set and minimize the reconstruction error. In order for better...
We propose a methodology for cross matching color face images and Short Wave Infrared (SWIR) face images reliably and accurately. We first adopt a recently designed image encoding and matching technique which is capable to encode face images in both visible and SWIR spectral bands. Encoding is performed in two steps. Images are initially filtered with a bank of Gabor filters. Then three local operators:...
3D face modeling from 2D face images is of significant importance for face analysis, animation and recognition. Previous research on this topic mainly focused on 3D face modeling from a single 2D face image; however, a single face image can only provide a limited description of a 3D face. In many applications, for example, law enforcement, multi-view face images are usually captured for a subject...
We present a framework, called uniqueness-based nonmatch estimates (UNE), which demonstrates the ability to improve face recognition performance of any face matcher. The first aspect of the framework is a novel metric for measuring the uniqueness of a given individual, called the impostor-based uniqueness measure (IUM). The UNE the maps face match scores from any any face matcher into non-match probability...
In this paper, to characterize and distinguish identical twins, three popular texture descriptors: i.e. local binary patterns (LBPs), gabor filters (GFs) and local gabor binary patterns (LGBPs) are employed to encode the normal components (x, y and z) of the 3D facial surfaces of identical twins respectively. A group of facial normal descriptors are thus achieved, including Normal Local Binary Patterns...
Recent works have investigated the robustness to spoofing attacks of multi-modal biometric systems in parallel fusion mode. Contrary to a common belief, it has been shown that they can be cracked by spoofing only one bio-metric trait. Robustness evaluation of multi-modal systems in serial fusion mode has not yet been investigated, instead. Thus, the aim of this paper is to comparatively evaluate the...
Gabor features have been extensively used for facial image analysis due to their powerful representation capabilities. This paper focuses on selecting and combining multiple Gabor classifiers that are trained on, for example, different scales and local regions. The system exploits curvature Gabor features in addition to conventional Gabor features. Final classifier is obtained by combining selected...
We investigate the application of similarity-based classification to biometric recognition, interpreting similarity functions used in biometric systems (i.e., matching algorithms) as kernel functions. This leads us to formulate biometric recognition as a distinct two-class classification problem for each client, which can be solved even when no representation of biometric samples in a feature space...
Face recognition across large pose changes is one of the hardest problems for automatic face recognition. Recently, approaches that use partial least squares (PLS) to compute pairwise pose-independent coupled subspaces have achieved good results on this problem. In this paper, we perform a thorough experimental analysis of the PLS approach for pose-invariant face recognition. We find that the use...
Face detection and Facial feature extraction are considered among the most studied topics in the field of biometrics. In real-world uncontrolled scenarios, high rate of false alarm is still a major problem. This paper presents a solution to reduce false alarm rate resulting from any generic face detector, through a fast post-processing algorithm based on utilizing a probabilistic framework for facial...
This paper investigates the problem of automatically steering one or more Narrow Field of View (NFOW) cameras to a target subject using only a single image from a reference NFOW camera, without the help of a Wide Field of View (WFOV) camera. To find the approximate distance of the subject from the reference camera, our algorithm uses information from facial biometrics, specifically the inter-pupil...
The matching performance of automated face recognition has significantly improved over the past decade. At the same time several challenges remain that significantly affect the deployment of such systems in security applications. In this work, we study the impact of a commonly used face altering technique that has received limited attention in the biometric literature, viz., non-permanent facial makeup...
The task of successfully matching face images obtained before and after plastic surgery is a challenging problem. The degree to which a face is altered depends on the type and number of plastic surgeries performed, and it is difficult to model such variations. Existing approaches use learning based methods that are either computationally expensive or rely on a set of training images. In this work,...
CAPTCHA is one of the Turing tests used to classify human users and automated scripts. Existing CAPTCHAs, especially text-based CAPTCHAs, are used in many applications, however they pose challenges due to language dependency and high attack rates. In this paper, we propose a face recognition-based CAPTCHA as a potential solution. To solve the CAPTCHA, users must correctly find one pair of human face...
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