This article proposes a novel Children-Computer Interaction (CCI) approach for the task of age group detection. This approach focuses on the automatic analysis of the time series generated from the interaction of the ...
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Imaging using millimeter waves (mmWs) has many advantages including the ability to penetrate obscurants, such as clothes and polymers. After having explored shape information retrieved from mmW images for person recog...
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Imaging using millimeter waves (mmWs) has many advantages including the ability to penetrate obscurants, such as clothes and polymers. After having explored shape information retrieved from mmW images for person recognition, in this paper we aim to gain some insight about the potential of using mmW texture information for the same task, considering not only the mmW face, but also mmW torso and mmW wholebody. We report experimental results using the mmW TNO database consisting of 50 individuals based on both hand-crafted and learned features from Alexnet and VGG-face pretrained convolutional neural networks (CNNs) models. First, we analyze the individual performance of three mmW body parts, concluding that: 1) mmW torso region is more discriminative than mmW face and the whole body; 2) CNN features produce better results compared to hand-crafted features on mmW faces and the entire body; and 3) hand-crafted features slightly outperform CNN features on mmW torso. In the second part of this paper, we analyze different multi-algorithmic and multi-modal techniques, including a novel CNN-based fusion technique, improving verification results to 2% EER and identification rank-1 results up to 99%. Comparative analyses with mmW body shape information and face recognition in the visible and NIR spectral bands are also reported.
Face recognition (FR) systems have a growing effect on critical decision-making processes. Recent works have shown that FR solutions show strong performance differences based on the user’s demographics. However, to e...
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This chapter provides an introduction to Presentation Attack Detection (PAD) in fingerprint biometrics, also coined anti-spoofing, describes early developments in this field, and briefly summarizes recent trends and o...
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This article presents SVC-onGoing, an on-going competition for on-line signature verification where researchers can easily benchmark their systems against the state of the art in an open common platform using large-sc...
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This paper describes the experimental framework and results of the IJCB 2022 Mobile Behavioral biometrics Competition (MobileB2C). The aim of MobileB2C is bench-marking mobile user authentication systems based on beha...
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ISBN:
(纸本)9781665463959
This paper describes the experimental framework and results of the IJCB 2022 Mobile Behavioral biometrics Competition (MobileB2C). The aim of MobileB2C is bench-marking mobile user authentication systems based on behavioral biometric traits transparently acquired by mobile devices during ordinary Human-Computer Interaction (HCI), using a novel public database, BehavePassDB 1 1 https://***/BiDAlab/MobileB2C_BehavePassDE, and a standard experimental protocol. The competition is divided into four tasks corresponding to typical user activities: keystroke, text reading, gallery swiping, and tapping. The data are composed of touchscreen data and several background sensor data simultaneously acquired. “Random” (different users with different devices) and “skilled” (different user on the same device attempting to imitate the legitimate one) impostor scenarios are considered. The results achieved by the participants show the feasibility of user authentication through behavioral biometrics, although this proves to be a non-trivial challenge. MobileB2C will be established as an on-going competition 2 2 https://***/view/mobileb2c/.
This paper proposes a method to generate the synthetic kinematic of signatures in 3D. The analysis of 3D signatures is becoming a hot topic due to the irruption of commercial off-the-shelf devices for easy acquisition...
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ISBN:
(纸本)9781665463959
This paper proposes a method to generate the synthetic kinematic of signatures in 3D. The analysis of 3D signatures is becoming a hot topic due to the irruption of commercial off-the-shelf devices for easy acquisition of 3D movements. However, the novelty of this technology reveals the scarce publicly available signatures in 3D, which hinder their de-velopment. A solution is the synthesis of Signatures in 3D. As a first step, this paper synthesizes the kinematics of 3D signatures based on the Kinematic Theory of Rapid Movements and its associated Sigma-Lognormal model in 3D. To evaluate the method, we regenerate signature databases with synthetic speed profiles in all genuine and forgeries found in two 3D signature databases. Then, we analyze the similarities in the performance of a signature verifier when real and synthetic signatures are used in random and skilled forgeries experiments.
This paper describes the experimental framework and results of the IJCB 2022 Mobile Behavioral biometrics Competition (MobileB2C). The aim of MobileB2C is benchmarking mobile user authentication systems based on behav...
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This paper describes the experimental framework and results of the ICDAR 2021 Competition on On-Line Signature Verification (SVC 2021). The goal of SVC 2021 is to evaluate the limits of on-line signature verification ...
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