Visual speech encoding based on facial landmark registration

Visual Speech Recognition (VSR) related studies largely ignore the use of state of the art approaches in facial landmark localization, and are also deficit of robust visual features and its temporal encoding. In this work, we propose a visual speech temporal encoding by integrating state of the art fast and accurate facial landmark detection based on ensemble of regression trees learned using gradient boosting. The main contribution of this work is in proposing a fast and simple encoding of visual speech features derived from vertically symmetric point pairs (VeSPP) of facial landmarks corresponding to lip regions, and demonstrating their usefulness in temporal sequence comparisons using Dynamic Time Warping. VSR can be either speaker dependent (SD) or speaker independent (SI), and each of them poses different kind of challenges. In this work, we consider the SD scenario, and obtain 82.65% recognition accuracy on OuluVS database. Unlike recent research in VSR which makes use of auxiliary information such as audio, depth and color channels, our approach does not impose such constraints

From biometric scores to forensic likelihood ratios

In this chapter, we describe the issue of the interpretation of forensic evidence from scores computed by a biometric system. This is one of themost important topics into the so-called area of forensic biometrics.We will show the importance of the topic, introducing some of the key concepts of forensic science with respect to the interpretation of results prior to their presentation in court, which is increasingly addressed by the computation of likelihood ratios (LR). We will describe the LR methodology, and will illustrate it with an example of the evaluation of fingerprint evidence in forensic conditions, by means of a fingerprint biometric system.</p

Anisotropy of the electric field gradient in two-dimensional alpha-MoO_(3) investigated by (57)^Mn((57)^Fe) emission mossbauer spectroscopy

Van der Waals alpha-MoO_(3) samples offer awide range of attractive catalytic, electronic, and optical properties. We present herein an emission Mossbauer spectroscopy (eMS) study of the electric-field gradient (EFG) anisotropy in crystalline free-standing alpha-MoO_(3) samples. Although alpha-MoO3 is a twodimensional (2D) material, scanning electron microscopy shows that the crystals are 0.5-5-mu m thick. The combination of X-ray diffraction and micro-Raman spectroscopy, performed after sample preparation, provided evidence of the phase purity and crystal quality of the samples. The eMS measurements were conducted following the implantation of (57)^Mn (t(1/ 2) = 1.5 min), which decays to the (57)^Fe, 14.4 keV Mossbauer state. The eMS spectra of the samples are dominated by a paramagnetic doublet (D1) with an angular dependence, pointing to the Fe^(2+) probe ions being in a crystalline environment. It is attributed to an asymmetric EFG at the eMS probe site originating from strong in-plane covalent bonds and weak out-of-plane van derWaals interactions in the 2D material. Moreover, a second broad component, D2, can be assigned to Fe^(3+) defects that are dynamically generated during the online measurements. The results are compared to ab initio simulations and are discussed in terms of the in-plane and out-of-plane interactions in the syste

Temperature Dependence of the Hyperfine Magnetic Field at Fe Sites in Ba-Doped BiFeO3 Thin Films Studied by Emission Mössbauer Spectroscopy

Emission 57Fe Mössbauer spectroscopy (eMS), following the implantation of radioactive 57Mn+ ions, has been used to study the temperature dependence of the hyperfine magnetic field at Fe sites in Ba-doped BiFeO3 (BFO) thin films. 57Mn β decays (t1/2 = 90 s) to the 14.4 keV Mössbauer state of 57Fe, thus allowing online eMS measurements at a selection of sample temperatures during Mn implantation. The eMS measurements were performed on two thin film BFO samples, 88 nm and 300 nm thick, and doped to 15% with Ba ions. The samples were prepared by pulsed laser deposition on SrTiO3 substrates. X-ray diffraction analyses of the samples showed that the films grew in a tetragonal distorted structure. The Mössbauer spectra of the two films, measured at absorber temperatures in the range 301 K–700 K, comprised a central pair of paramagnetic doublets and a magnetic sextet feature in the wings. The magnetic component was resolved into (i) a component attributed to hyperfine interactions at Fe3+ ions located in octahedral sites (Bhf); and (ii) to Fe3+ ions in implantation induced lattice defects, which were characterized by a distribution of the magnetic field BDistr. The hyperfine magnetic field at the Fe probes in the octahedral site has a room temperature value of Bhf = 44.5(9) T. At higher sample temperatures, the Bhf becomes much weaker, with the Fe3+ hyperfine magnetic contribution disappearing above 700 K. Simultaneous analysis of the Ba–BFO eMS spectra shows that the variation of the hyperfine field with temperature follows the Brillouin curve for S = 5/2.This work has received the financial support from the Federal Ministry of Education and Research (BMBF) through grants 05K16PGA, 05K22PGA, 05K16SI1, 05K19SI1 “eMIL” and “eMMA”; from the European Union’s Horizon 2020 Framework research and innovation program under grant agreement no. 654002 (ENSAR2) and 101057511 (EURO-LABS); from the Ministry of Economy and Competitiveness Consolider—Ingenio Project CSD2009 0013 “IMAGINE” Spain, and Banco Santander-UCM, project PR87/19-22613; from the Austrian Science Fund (FWF) through projects P26830 and P31423, from the Icelandic University Research Fund; from the National Research Foundation (South Africa); and from the Ministry of Economy and Competitiveness (MINECO/FEDER) for the Grant No. RTI2018-094683-B-C55 C55 and Basque Government Grant No. IT-1500-22

Anisotropy of the electric field gradient in two-dimensional α-MoO3 investigated by 57Mn(57Fe) emission Mössbauer spectroscopy

Van der Waals α-MoO3 samples offer a wide range of attractive catalytic, electronic, and optical properties. We present herein an emission Mössbauer spectroscopy (eMS) study of the electric-field gradient (EFG) anisotropy in crystalline free-standing α-MoO3 samples. Although α-MoO3 is a two-dimensional (2D) material, scanning electron microscopy shows that the crystals are 0.5-5-µm thick. The combination of X-ray diffraction and micro-Raman spectroscopy, performed after sample preparation, provided evidence of the phase purity and crystal quality of the samples. The eMS measurements were conducted following the implantation of 57Mn (t1/2 = 1.5 min), which decays to the 57Fe, 14.4 keV Mössbauer state. The eMS spectra of the samples are dominated by a paramagnetic doublet (D1) with an angular dependence, pointing to the Fe2+ probe ions being in a crystalline environment. It is attributed to an asymmetric EFG at the eMS probe site originating from strong in-plane covalent bonds and weak out-of-plane van der Waals interactions in the 2D material. Moreover, a second broad component, D2, can be assigned to Fe3+ defects that are dynamically generated during the online measurements. The results are compared to ab initio simulations and are discussed in terms of the in-plane and out-of-plane interactions in the system

Integrating rare minutiae in generic fingerprint matchers for forensics

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. R. P. Krish, J. Fierrez and D. Ramos, "Integrating rare minutiae in generic fingerprint matchers for forensics," 2015 IEEE International Workshop on Information Forensics and Security (WIFS), Rome, 2015, pp. 1-6. doi: 10.1109/WIFS.2015.7368557Automated Fingerprint Identification Systems (AFIS) are commonly used by law enforcement agencies to narrow down the possible suspects from a criminal database. AFIS do not use all discriminatory features available in fingerprints but typically use only some types of features automatically extracted by a feature extraction algorithm. Latent fingerprints obtained from crime scenes are usually partial in nature which results to only very few number of reliable minutiae. Comparing a partial minutiae pattern to a full minutiae pattern is a difficult problem. Towards solving this challenge, we propose a method that exploits extended fingerprint features (unusual/rare minutiae) not commonly considered in typical minutiae-based matchers. The method we propose in this work can be combined with any existing minutiae-based matcher. We first compute a quantitative measure based on least squares between latent and tenprint minutiae points, with rare minutia feature as reference point. Then the similarity score of the reference minutiae-based matcher is modified based on the least square quantitative measure. The modified similarity score thus obtained incorporates the contribution of rare minutia features. We use a realistic forensic fingerprint casework database in our experiments which contains rare minutia features obtained from Guardia Civil, the Spanish law enforcement agency. Experiments are conducted using two reference minutiae-based matchers, namely: NIST-Bozorth3 and VeriFinger. We report a significant improvement in the rank identification accuracies when the reference minutiae matchers are augmented with our proposed algorithm based on rare minutia features.R.K. was supported by a Marie Curie Fellowship under project BBfor2 (FP7-ITN-238803) from EU. This work has also been partially supported by Spanish Guardia Civil, project Bio-Shield (TEC2012-34881) from Spanish MINECO, and project BEAT (FP7-SEC-284989) from EU

R.P.: Towards Regional Fusion for High-Resolution Palmprint Recognition

Abstract-The existing high resolution palmprint matching algorithms essentially follow the minutiae-based fingerprint matching strategy and focus on full-to-full/partial-to-full palmprint comparison. These algorithms would face problems when they are applied to forensic palmprint recognition where latent marks have much smaller area than full palmprints. Therefore, towards forensic scenarios, we propose a novel matching strategy based on regional fusion for high resolution palmprint recognition using regions segmented by major creases features. The matching strategy includes two stages: 1) region-to-region palmprint comparison; 2) regional fusion at score level. We first studied regional discriminability of a high resolution palmprint under the concept of three regions, i.e., interdigital, hypothenar and thenar, which is the most significant difference between palmprits and fingerprints. Then we implemented regional fusion based on logistic regression at score level using region-to-region comparison scores obtained by a commercial SDK, MegaMatcher 4.0. Significant improvement of recognition accuracy is achieved by regional fusion on a public high resolution palmprint database THUPALMLAB. The EER of logistic regression based regional fusion is 0.25%, while the EER of full-to-full palmprint comparison is 1%

Towards regional fusion for high-resolution palmprint recognition

Abstract—The existing high resolution palmprint matching algorithms essentially follow the minutiae-based fingerprint matching strategy and focus on full-to-full/partial-to-full palmprint comparison. These algorithms would face problems when they are applied to forensic palmprint recognition where latent marks have much smaller area than full palmprints. Therefore, towards forensic scenarios, we propose a novel matching strategy based on regional fusion for high resolution palmprint recognition using regions segmented by major creases features. The matching strategy includes two stages: 1) region-to-region palmprint comparison; 2) regional fusion at score level. We first studied regional discriminability of a high resolution palmprint under the concept of three regions, i.e., interdigital, hypothenar and thenar, which is the most significant difference between palmprits and fingerprints. Then we implemented regional fusion based on logistic regression at score level using region-to-region comparison scores obtained by a commercial SDK, MegaMatcher 4.0. Significant improvement of recognition accuracy is achieved by regional fusion on a public high resolution palmprint database THUPALMLAB. The EER of logistic regression based regional fusion is 0.25%, while the EER of full-to-full palmprint comparison is 1%. Keywords-High resolution palmprints; regional fusion. I

Automatic Region Segmentation for High-resolution Palmprint Recognition: Towards Forensic Scenarios

Abstract—Recently, a novel matching strategy based on regional fusion for high resolution palmprint recognition arises for both forensic and civil applications, under the concept of different regional discriminability of three palm regions, i.e., interdigital, hypothenar and thenar. This matching strategy requires accurate automatic region segmentation techniques since manual region segmentation is time consuming. In this work, we develop automatic region segmentation techniques based on datum point detection for high-resolution palmprint recognition which can be further applied to forensic applications. Firstly, Canny edge detector is applied to a full palmprint to obtain gradient magnitudes and strong edges. Then a first datum point, i.e., the endpoint of heart line, is detected by using convex hull on gradient magnitude image and its left/right differential image and strong edge image. A second datum point, i.e., the endpoint of life line, is estimated based on the position and direction of the first datum point and statistical average distance between the two datum points. Finally, segmented palm regions are generated based on the two datum points and their perpendicular bisector. To evaluate the accuracy of our region segmentation method, we compare the automatic segmentation with manual segmentation performed on a public high resolution palmprint database THUPALMLAB with full palmprint images. The regional error rates of interdigital, thenar and hypothenar regions are 15.72%, 17.05 % and 21.38 % respectively. And the total error rate is 19.54 % relative to full palmprint images. I

Dynamic Signature Verification on Smart Phones

Abstract. This work is focused on dynamic signature verification for state-of-the-art smart phones, including performance evaluation. The analysis was performed on database consisting of 25 users and 500 signatures in total acquired with Samsung Galaxy Note. The verification algorithm tested combines two approaches: feature based (using Mahalanobis distance) and function based (using DTW), and the results are shown in terms of EER values. A number of experimental findings associated with signature verification in this scenario are obtained, e.g., the dominant challenge associated with the intra-class variability across time. As a result of the algorithm adaptation to the mobile scenario, the use of a state-of-the-art smart phone, and contrarily to what has been evidenced in previous works, we finally demonstrate that signature verification on smart phones can result in a similar verification performance compared to one obtained using more ergonomic stylus-based pen tablets. In particular, the best result achieved is an EER of 0.525%