Journal ArticleDOI
Ocular biometrics
TLDR
A path forward is proposed to advance the research on ocular recognition by improving the sensing technology, heterogeneous recognition for addressing interoperability, utilizing advanced machine learning algorithms for better representation and classification, and developing algorithms for ocular Recognition at a distance.About:
This article is published in Information Fusion.The article was published on 2015-11-01. It has received 138 citations till now. The article focuses on the topics: Iris recognition & Biometrics.read more
Citations
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Journal ArticleDOI
Iris Recognition With Off-the-Shelf CNN Features: A Deep Learning Perspective
TL;DR: It is shown that the off-the-shelf CNN features, while originally trained for classifying generic objects, are also extremely good at representing iris images, effectively extracting discriminative visual features and achieving promising recognition results on two iris datasets: ND-CrossSensor-2013 and CASIA-Iris-Thousand.
Journal ArticleDOI
Long range iris recognition
TL;DR: This paper reviews the state-of-the-art design and implementation of iris-recognition-at-a-distance (IAAD) systems and presents a complete solution to the design problem of an IAAD system, from both hardware and algorithmic perspectives.
Journal ArticleDOI
Tumor co-segmentation in PET/CT using multi-modality fully convolutional neural network.
TL;DR: This study proposed a novel multi-modality segmentation method based on a 3D fully convolutional neural network (FCN), which is capable of taking account of both PET and CT information simultaneously for tumor segmentation and achieved significantly performance gain over CNN-based methods and traditional methods.
Journal ArticleDOI
Overview of the combination of biometric matchers
Alessandra Lumini,Loris Nanni +1 more
TL;DR: Several systems and architectures related to the combination of biometric systems, both unimodal and multimodal, are overviews, classifying them according to a given taxonomy, and a case study for the experimental evaluation of methods for biometric fusion at score level is presented.
Journal ArticleDOI
A survey on periocular biometrics research
TL;DR: This work is expected to provide an insight of the most relevant issues in periocular biometrics, giving a comprehensive coverage of the existing literature and current state of the art.
References
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Journal ArticleDOI
High confidence visual recognition of persons by a test of statistical independence
TL;DR: A method for rapid visual recognition of personal identity is described, based on the failure of a statistical test of independence, which implies a theoretical "cross-over" error rate of one in 131000 when a decision criterion is adopted that would equalize the false accept and false reject error rates.
Journal ArticleDOI
Multi-PIE
TL;DR: This paper introduces the database, describes the recording procedure, and presents results from baseline experiments using PCA and LDA classifiers to highlight similarities and differences between PIE and Multi-PIE.
Proceedings Article
Saliency Based on Information Maximization
Neil D. B. Bruce,John K. Tsotsos +1 more
TL;DR: A model of bottom-up overt attention is proposed based on the principle of maximizing information sampled from a scene and is achieved in a neural circuit, which is demonstrated as having close ties with the circuitry existent in die primate visual cortex.
Proceedings Article
Multi-PIE
TL;DR: The CMU Multi-PIE database as mentioned in this paper contains 337 subjects, imaged under 15 view points and 19 illumination conditions in up to four recording sessions, with a limited number of subjects, a single recording session and only few expressions captured.
Book
Handbook of Multibiometrics
TL;DR: Details multi-modal biometrics and its exceptional utility for increasingly reliable human recognition systems and the substantial advantages of multimodal systems over conventional identification methods.