Such techniques are designed to restore generic images and therefore do not exploit the specific structure found in biometric images (e. g. iris or faces), which causes the solution to be sub-optimal.
To help in counteracting such issues, we contribute with a database of facial images that includes several manipulations.
We describe a technical solution implemented at Halmstad University to automatise assessment and reporting of results of paper-based quiz exams.
With ten enrolment samples, the Top-1 accuracy with deep features is around 94%, and reaches nearly 100% by Top-10.
Biometric technology has been increasingly deployed in the past decade, offering greater security and convenience than traditional methods of personal recognition.
no code implementations • 17 Nov 2021 • Norman Poh, Thirimachos Bourlai, Josef Kittler, Lorene Allano, Fernando Alonso-Fernandez, Onkar Ambekar, John Baker, Bernadette Dorizzi, Omolara Fatukasi, Julian Fierrez, Harald Ganster, Javier Ortega-Garcia, Donald Maurer, Albert Ali Salah, Tobias Scheidat, Claus Vielhauer
The cost-sensitive evaluation, on the other hand, investigates how well a fusion algorithm can perform given restricted computation and in the presence of software and hardware failures, resulting in errors such as failure-to-acquire and failure-to-match.
no code implementations • 17 Nov 2021 • Javier Ortega-Garcia, Julian Fierrez, Fernando Alonso-Fernandez, Javier Galbally, Manuel R Freire, Joaquin Gonzalez-Rodriguez, Carmen Garcia-Mateo, Jose-Luis Alba-Castro, Elisardo Gonzalez-Agulla, Enrique Otero-Muras, Sonia Garcia-Salicetti, Lorene Allano, Bao Ly-Van, Bernadette Dorizzi, Josef Kittler, Thirimachos Bourlai, Norman Poh, Farzin Deravi, Ming NR Ng, Michael Fairhurst, Jean Hennebert, Andreas Humm, Massimo Tistarelli, Linda Brodo, Jonas Richiardi, Andrezj Drygajlo, Harald Ganster, Federico M Sukno, Sri-Kaushik Pavani, Alejandro Frangi, Lale Akarun, Arman Savran
It is comprised of more than 600 individuals acquired simultaneously in three scenarios: 1) over the Internet, 2) in an office environment with desktop PC, and 3) in indoor/outdoor environments with mobile portable hardware.
One of the open issues in fingerprint verification is the lack of robustness against image-quality degradation.
no code implementations • 2 Nov 2021 • Julian Fierrez, Javier Galbally, Javier Ortega-Garcia, Manuel R Freire, Fernando Alonso-Fernandez, Daniel Ramos, Doroteo Torre Toledano, Joaquin Gonzalez-Rodriguez, Juan A Siguenza, Javier Garrido-Salas, E Anguiano, Guillermo Gonzalez-de-Rivera, Ricardo Ribalda, Marcos Faundez-Zanuy, JA Ortega, Valentín Cardeñoso-Payo, A Viloria, Carlos E Vivaracho, Q Isaac Moro, Juan J Igarza, J Sanchez, Inmaculada Hernaez, Carlos Orrite-Urunuela, Francisco Martinez-Contreras, Juan José Gracia-Roche
A new multimodal biometric database, acquired in the framework of the BiosecurID project, is presented together with the description of the acquisition setup and protocol.
To counteract the mentioned issues and allow fundamental studies with a common public benchmark, we contribute with an annotated multi-sensor database for drone detection that includes infrared and visible videos and audio files.
A new software-based liveness detection approach using a novel fingerprint parameterization based on quality related features is proposed.
We extract characteristic SIFT feature points in scale space and perform matching based on the texture information around the feature points using the SIFT operator.
In this contribution, the vulnerabilities of iris-based recognition systems to direct attacks are studied.
This work is aimed at creating a system that can classify different types of plastics by using picture analysis, in particular, black plastics of the type Polystyrene (PS) and Acrylonitrile Butadiene Styrene (ABS).
Although there is room for improvement, when neither U-NET reconstruction nor training with filtered images is applied, the accuracy with filters that severely occlude the eye is <72% (identification) and >12% (EER)
This paper describes AI perspectives in SCC and gives an overview of AI-based technologies used in traffic to enable road vehicle automation and smart traffic control.
Also, the use of mobile devices has exploded, with the pandemic further accelerating the migration to digital services.
Recognition experiments are done using a number of off-the-shelf periocular comparators based both on hand-crafted features and CNN descriptors.
With a large number of training Tweets (>500), a good accuracy (Rank-5>80%) is achievable with only a few dozens of test Tweets, even with several thousands of authors.
Accordingly, we address the challenge of developing a lightweight face recognition network of just a few megabytes that can operate with sufficient accuracy in comparison to much larger models.
Besides the common video and audio sensors, the system also includes a thermal infrared camera, which is shown to be a feasible solution to the drone detection task.
To that end, a novel multi-scale minutia model where location, direction, and scale of minutia parameters are steerable, without the creation of uncontrollable minutia is also presented.
Accordingly, the goal is to develop a solution which can measure the operational state using the input from a video camera capturing a factory floor.
This paper describes the implementation of a system to recognize employees and visitors wanting to gain access to a physical office through face images and speech-to-text recognition.
In this work, we aim at identifying authors of tweet messages, which are limited to 280 characters.
Cross-spectral verification remains a big issue in biometrics, especially for the ocular area due to differences in the reflected features in the images depending on the region and spectrum used.
Experiments are also reported with a database of VIS images from different smartphones.
We report significant improvements in the rank identification accuracies when these minutiae matchers are augmented with our proposed algorithm based on rare minutiae features.
Action and intention recognition of pedestrians in urban settings are challenging problems for Advanced Driver Assistance Systems as well as future autonomous vehicles to maintain smooth and safe traffic.
This paper describes an approach of creating a system identifying fruit and vegetables in the retail market using images captured with a video camera attached to the system.