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Automated and accurate biometrics identification using periocular imaging has wide range of applications from human surveillance to improving performance for iris recognition systems, especially under less-constrained imaging environment. Restricted Boltzmann Machine is a generative stochastic neural network that can learn the probability distribution over its set of inputs. As a convolutional version...
Kinship verification from facial images is an interesting and challenging problem in computer vision, and there are very limited attempts on tackle this problem in the literature. In this paper, we propose a new neighborhood repulsed metric learning (NRML) method for kinship verification. Motivated by the fact that interclass samples (without a kinship relation) with higher similarity usually lie...
The current challenges to developing commercial Ocular Biometric systems are to create applications that tolerate unconstrained environments. Designs for sensors, user interfaces, and algorithms must perform well under variable illumination, poses, and camera distances, with low-quality images, and within other real-world conditions. Practical deployment requires interoperability of data and processing...
The development of a fully automatic facial expression recognition system is an open problem. Its implications are very important, with applications ranging from machine intelligence and interaction to psychology research. In order to obtain a viable system, it is necessary to get valid parameters to characterize the facial expression in an image or a video sequence. Several different techniques have...
There is mounting evidence about the benefit of tailoring a biometric authentication system to each user by postprocessing the system output at the score level, also known as client-specific score normalisation. Examples of these procedures are Z-norm and F-norm. These procedures can calibrate the uneven hypothesis space such that the dispropotionate false acceptance and false rejection errors are...
Research in computer science evolves very quickly. In order to prove the efficiency of a new algorithm, it is generally necessary to show some results on a large and significant benchmark used in the state of the art. This fact has for consequence the need of a large computation capability in a research laboratory. We address in this paper the performance evaluation of biometric systems through distributed...
Increasing use of computerized systems in our daily lives creates new adversarial opportunities for which complex mechanisms are exploited to mend the rapid development of new attacks. Behavioral Biometrics appear as one of the promising response to these attacks. But it is a relatively new research area, specific frameworks for evaluation and development of behavioral biometrics solutions could not...
Biometric authentication methods are being increasingly used for many types of applications. Since such methods necessitate humans to interact with a device, effective implementation requires consideration of the perceptions and responses of end users. Towards this goal, we present in this paper a modality-independent evaluation methodology to study users' acceptance and satisfaction of biometric...
This paper presents an efficient IrisCode classifier, built from phase features which uses AdaBoost for the selection of Gabor wavelets bandwidths. The final iris classifier consists of a weighted contribution of weak classifiers. As weak classifiers we use 3-split decision trees that identify a candidate based on the Levenshtein distance between phase vectors of the respective iris images. Our experiments...
In this paper we explore the use of shapes of noses for performing partial human biometrics. The basic idea is to represent nasal surfaces using indexed collections of iso-curves, and to analyze shapes of noses by comparing their corresponding curves. We extend past work in Riemannian analysis of shapes of closed curves in R3 to obtain a similar Riemannian analysis for nasal surfaces. In particular,...
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