no code implementations • 21 Aug 2024 • Melissa R Dale, Anil Jain, Arun Ross
We show that the application of various score imputation methods along with simple sum fusion can improve recognition accuracy, even when the proportion of missing scores increases to 90%.
no code implementations • 20 Aug 2024 • Nitish Shukla, Arun Ross
The goal is to generate an image that can be matched with two identities thereby undermining the security of a face recognition system.
no code implementations • 15 Aug 2024 • Melissa R Dale, Elliot Singer, Bengt J. Borgström, Arun Ross
Imputation is a promising technique in multibiometric systems for replacing missing data.
1 code implementation • 14 Aug 2024 • Sudipta Banerjee, Arun Ross
Near-duplicate images are often generated when applying repeated photometric and geometric transformations that produce imperceptible variants of the original image.
no code implementations • 9 Aug 2024 • Parisa Farmanifard, Arun Ross
This study utilizes the advanced capabilities of the GPT-4 multimodal Large Language Model (LLM) to explore its potential in iris recognition - a field less common and more specialized than face recognition.
no code implementations • 26 Apr 2024 • Shivangi Yadav, Arun Ross
In this paper, we present a comprehensive review of state-of-the-art GAN-based synthetic iris image generation techniques, evaluating their strengths and limitations in producing realistic and useful iris images that can be used for both training and testing iris recognition systems and presentation attack detectors.
no code implementations • 24 Apr 2024 • Bharat Yalavarthi, Arjun Ramesh Kaushik, Arun Ross, Vishnu Boddeti, Nalini Ratha
These features denote embeddings in latent space and are often stored as templates in a face recognition system.
1 code implementation • 9 Feb 2024 • Parisa Farmanifard, Arun Ross
Iris segmentation is a critical component of an iris biometric system and it involves extracting the annular iris region from an ocular image.
1 code implementation • 29 Jan 2024 • Morgan Sandler, Hyesun Choung, Arun Ross, Prabu David
The research also contributes a novel, companion ChatGPT-generated dataset of conversations between two independent chatbots, which were designed to replicate a corpus of human conversations available for open access and used widely in AI research on language modeling.
no code implementations • 21 Nov 2023 • Darshika Jauhari, Renu Sharma, Cunjian Chen, Nelson Sepulveda, Arun Ross
We observe that the addition of VO2 films on the surface of artificial eyes can cause the PA detection methods to misclassify them as bonafide eyes in some cases.
1 code implementation • 21 Nov 2023 • Renu Sharma, Redwan Sony, Arun Ross
In this work, we assess the sensitivity of DNNs against perturbations to their weight and bias parameters.
no code implementations • 20 Nov 2023 • Sudipta Banerjee, Anubhav Jain, Zehua Jiang, Nasir Memon, Julian Togelius, Arun Ross
A dictionary attack in a biometric system entails the use of a small number of strategically generated images or templates to successfully match with a large number of identities, thereby compromising security.
no code implementations • 5 Sep 2023 • Sushanta K. Pani, Anurag Chowdhury, Morgan Sandler, Arun Ross
In a biometric system, each biometric sample or template is typically associated with a single identity.
no code implementations • 3 Aug 2023 • Vishnu Naresh Boddeti, Gautam Sreekumar, Arun Ross
Our capacity estimates indicate that (a) under ArcFace representation at a false acceptance rate (FAR) of 0. 1%, StyleGAN3 and DCFace have a capacity upper bound of $1. 43\times10^6$ and $1. 190\times10^4$, respectively; (b) the capacity reduces drastically as we lower the desired FAR with an estimate of $1. 796\times10^4$ and $562$ at FAR of 1% and 10%, respectively, for StyleGAN3; (c) there is no discernible disparity in the capacity w. r. t gender; and (d) for some generative models, there is an appreciable disparity in the capacity w. r. t age.
1 code implementation • 7 Jul 2023 • Debasmita Pal, Arun Ross
Our method helps render the appearance of forest sites specific to a greenness value.
no code implementations • 29 Jun 2023 • Feng Liu, Ryan Ashbaugh, Nicholas Chimitt, Najmul Hassan, Ali Hassani, Ajay Jaiswal, Minchul Kim, Zhiyuan Mao, Christopher Perry, Zhiyuan Ren, Yiyang Su, Pegah Varghaei, Kai Wang, Xingguang Zhang, Stanley Chan, Arun Ross, Humphrey Shi, Zhangyang Wang, Anil Jain, Xiaoming Liu
Whole-body biometric recognition is an important area of research due to its vast applications in law enforcement, border security, and surveillance.
no code implementations • 21 May 2023 • Shivangi Yadav, Arun Ross
To overcome these issues, we propose iWarpGAN that disentangles identity and style in the context of the iris modality by using two transformation pathways: Identity Transformation Pathway to generate unique identities from the training set, and Style Transformation Pathway to extract the style code from a reference image and output an iris image using this style.
1 code implementation • 13 May 2023 • Morgan Sandler, Arun Ross
The accuracy of automated speaker recognition is negatively impacted by change in emotions in a person's speech.
no code implementations • 28 Dec 2022 • Fernando Alonso-Fernandez, Josef Bigun, Julian Fierrez, Naser Damer, Hugo Proença, Arun Ross
Periocular refers to the externally visible region of the face that surrounds the eye socket.
1 code implementation • 15 Nov 2022 • Morgan Sandler, Arun Ross
On the task of speech emotion detection, we obtain 80. 8% ACC with acted emotion samples from CREMA-D, 81. 2% ACC with semi-natural emotion samples in IEMOCAP, and 66. 9% ACC with natural emotion samples in MSP-Podcast.
no code implementations • 7 Sep 2022 • Sudipta Banerjee, Prateek Jaiswal, Arun Ross
In this work, we propose a novel de-morphing method that can recover images of both identities simultaneously from a single morphed face image without needing a reference image or prior information about the morphing process.
no code implementations • 7 Sep 2022 • Sudipta Banerjee, Aditi Aggarwal, Arun Ross
Impact due to demographic factors such as age, sex, race, etc., has been studied extensively in automated face recognition systems.
no code implementations • 19 Aug 2022 • Pedro C. Neto, Tiago Gonçalves, João Ribeiro Pinto, Wilson Silva, Ana F. Sequeira, Arun Ross, Jaime S. Cardoso
As two sides of the same coin, causality and explainable artificial intelligence (xAI) were initially proposed and developed with different goals.
Explainable artificial intelligence Explainable Artificial Intelligence (XAI)
1 code implementation • 15 Aug 2022 • Luke Sperling, Nalini Ratha, Arun Ross, Vishnu Naresh Boddeti
This paper proposes a non-interactive end-to-end solution for secure fusion and matching of biometric templates using fully homomorphic encryption (FHE).
no code implementations • 29 Mar 2022 • Renu Sharma, Arun Ross
The performance of face recognition systems can be negatively impacted in the presence of masks and other types of facial coverings that have become prevalent due to the COVID-19 pandemic.
no code implementations • 23 Mar 2022 • Hyesun Choung, Prabu David, Arun Ross
This paper addresses this need by explaining the role of trust on the intention to use AI technologies.
no code implementations • 12 Jan 2022 • David Anghelone, Cunjian Chen, Arun Ross, Antitza Dantcheva
Secondly, we discuss the appropriate spectral bands for face recognition and discuss recent CFR methods, placing emphasis on deep neural networks.
no code implementations • 9 Jan 2022 • Kien Nguyen, Clinton Fookes, Sridha Sridharan, YingLi Tian, Feng Liu, Xiaoming Liu, Arun Ross
The rapid emergence of airborne platforms and imaging sensors are enabling new forms of aerial surveillance due to their unprecedented advantages in scale, mobility, deployment and covert observation capabilities.
no code implementations • 5 Jul 2021 • Sudipta Banerjee, Arun Ross
We performed experiments on AMSL face morph, MorGAN, and EMorGAN datasets to demonstrate the effectiveness of the proposed method.
no code implementations • 8 Apr 2021 • Richard Plesh, Keivan Bahmani, Ganghee Jang, David Yambay, Ken Brownlee, Timothy Swyka, Peter Johnson, Arun Ross, Stephanie Schuckers
This paper demonstrates the viability of utilizing a sensor with time-series and color-sensing capabilities to improve the robustness of a traditional fingerprint sensor and introduces a comprehensive fingerprint dataset with over 36, 000 image sequences and a state-of-the-art set of spoofing techniques.
no code implementations • 2 Jan 2021 • Sudipta Banerjee, Arun Ross
In this work, we propose a method to simultaneously perform (i) biometric recognition (i. e., identify the individual), and (ii) device recognition, (i. e., identify the device) from a single biometric image, say, a face image, using a one-shot schema.
1 code implementation • 9 Dec 2020 • Anurag Chowdhury, Arun Ross, Prabu David
Automatic speaker recognition algorithms typically characterize speech audio using short-term spectral features that encode the physiological and anatomical aspects of speech production.
no code implementations • 4 Dec 2020 • Shivangi Yadav, Arun Ross
The Styling Network helps the generator to drive the translation of images from a source domain to a reference domain and generate synthetic images with style characteristics of the reference domain.
no code implementations • 23 Nov 2020 • Kien Nguyen, Clinton Fookes, Sridha Sridharan, Arun Ross
Unlike the problem of general object recognition, where real-valued neural networks can be used to extract pertinent features, iris recognition depends on the extraction of both phase and magnitude information from the input iris texture in order to better represent its biometric content.
no code implementations • 23 Oct 2020 • Cunjian Chen, Arun Ross
Two types of attention modules are independently appended on top of the last convolutional layer of the backbone network.
no code implementations • 22 Oct 2020 • Renu Sharma, Arun Ross
In this paper, we propose the use of Optical Coherence Tomography (OCT) imaging for the problem of iris presentation attack (PA) detection.
no code implementations • 17 Sep 2020 • Sudipta Banerjee, Arun Ross
The principle of Photo Response Non Uniformity (PRNU) is often exploited to deduce the identity of the smartphone device whose camera or sensor was used to acquire a certain image.
no code implementations • 1 Sep 2020 • Priyanka Das, Joseph McGrath, Zhaoyuan Fang, Aidan Boyd, Ganghee Jang, Amir Mohammadi, Sandip Purnapatra, David Yambay, Sébastien Marcel, Mateusz Trokielewicz, Piotr Maciejewicz, Kevin Bowyer, Adam Czajka, Stephanie Schuckers, Juan Tapia, Sebastian Gonzalez, Meiling Fang, Naser Damer, Fadi Boutros, Arjan Kuijper, Renu Sharma, Cunjian Chen, Arun Ross
Launched in 2013, LivDet-Iris is an international competition series open to academia and industry with the aim to assess and report advances in iris Presentation Attack Detection (PAD).
no code implementations • 26 Aug 2020 • Anurag Chowdhury, Arun Ross
The purpose of such a filterbank is to extract features robust to non-ideal audio conditions, such as degraded, short duration, and multi-lingual speech.
no code implementations • 8 Aug 2020 • Anurag Chowdhury, Austin Cozzo, Arun Ross
We also evaluate the effect of gender and language on speaker recognition performance, both in spoken and singing voice data.
2 code implementations • 2 Jul 2020 • Renu Sharma, Arun Ross
An iris recognition system is vulnerable to presentation attacks, or PAs, where an adversary presents artifacts such as printed eyes, plastic eyes, or cosmetic contact lenses to circumvent the system.
no code implementations • 21 Feb 2020 • Sudipta Banerjee, Arun Ross
We also utilize the same basis functions to model geometric transformations and deep-learning based transformations.
no code implementations • 2 Jan 2020 • Vahid Mirjalili, Sebastian Raschka, Arun Ross
Further, PrivacyNet allows a person to choose specific attributes that have to be obfuscated in the input face images (e. g., age and race), while allowing for other types of attributes to be extracted (e. g., gender).
no code implementations • 12 May 2019 • Arun Ross, Sudipta Banerjee, Cunjian Chen, Anurag Chowdhury, Vahid Mirjalili, Renu Sharma, Thomas Swearingen, Shivangi Yadav
The need for reliably determining the identity of a person is critical in a number of different domains ranging from personal smartphones to border security; from autonomous vehicles to e-voting; from tracking child vaccinations to preventing human trafficking; from crime scene investigation to personalization of customer service.
1 code implementation • 9 May 2019 • Olly Styles, Arun Ross, Victor Sanchez
In this work, we present a deep learning approach for pedestrian trajectory forecasting using a single vehicle-mounted camera.
no code implementations • 3 May 2019 • Vahid Mirjalili, Sebastian Raschka, Arun Ross
In this regard, Semi-Adversarial Networks (SAN) have recently emerged as a method for imparting soft-biometric privacy to face images.
no code implementations • 3 Mar 2019 • Cunjian Chen, Arun Ross
Designing face recognition systems that are capable of matching face images obtained in the thermal spectrum with those obtained in the visible spectrum is a challenging problem.
no code implementations • 8 Feb 2019 • Maneet Singh, Richa Singh, Arun Ross
A comprehensive review of techniques incorporating ancillary information in the biometric recognition pipeline is also presented.
no code implementations • 16 Jan 2019 • Debayan Deb, Arun Ross, Anil K. Jain, Kwaku Prakah-Asante, K. Venkatesh Prasad
Prevailing user authentication schemes on smartphones rely on explicit user interaction, where a user types in a passcode or presents a biometric cue such as face, fingerprint, or iris.
no code implementations • 31 Aug 2018 • Sudipta Banerjee, Vahid Mirjalili, Arun Ross
The principle of Photo Response Non-Uniformity (PRNU) is used to link an image with its source, i. e., the sensor that produced it.
no code implementations • 31 Jul 2018 • Vahid Mirjalili, Sebastian Raschka, Arun Ross
Recent research has proposed the use of Semi Adversarial Networks (SAN) for imparting privacy to face images.
1 code implementation • 4 May 2018 • Denton Bobeldyk, Arun Ross
Recent research has explored the possibility of automatically deducing information such as gender, age and race of an individual from their biometric data.
2 code implementations • 2017 IEEE International Conference on Big Data (Big Data) 2017 • Thomas Swearingen, Will Drevo, Bennett Cyphers, Alfredo Cuesta-Infante, Arun Ross, Kalyan Veeramachaneni
In this paper, we present Auto-Tuned Models, or ATM, a distributed, collaborative, scalable system for automated machine learning.
1 code implementation • 1 Dec 2017 • Vahid Mirjalili, Sebastian Raschka, Anoop Namboodiri, Arun Ross
In this paper, we design and evaluate a convolutional autoencoder that perturbs an input face image to impart privacy to a subject.
no code implementations • 25 Oct 2017 • Veeru Talreja, Terry Ferrett, Matthew C. Valenti, Arun Ross
This paper presents a framework for Biometrics-as-a-Service (BaaS) that performs biometric matching operations in the cloud, while relying on simple and ubiquitous consumer devices such as smartphones.
no code implementations • 21 May 2017 • Philip Bontrager, Aditi Roy, Julian Togelius, Nasir Memon, Arun Ross
The proposed method, referred to as Latent Variable Evolution, is based on training a Generative Adversarial Network on a set of real fingerprint images.