Search Results for author: Patrick Flynn

Found 27 papers, 6 papers with code

SiNC+: Adaptive Camera-Based Vitals with Unsupervised Learning of Periodic Signals

no code implementations20 Apr 2024 Jeremy Speth, Nathan Vance, Patrick Flynn, Adam Czajka

We present the first non-contrastive unsupervised learning framework for signal regression to mitigate the need for labelled video data.

Measuring Domain Shifts using Deep Learning Remote Photoplethysmography Model Similarity

no code implementations12 Apr 2024 Nathan Vance, Patrick Flynn

Domain shift differences between training data for deep learning models and the deployment context can result in severe performance issues for models which fail to generalize.

Deep Learning Model Selection

Refining Remote Photoplethysmography Architectures using CKA and Empirical Methods

no code implementations9 Jan 2024 Nathan Vance, Patrick Flynn

Model architecture refinement is a challenging task in deep learning research fields such as remote photoplethysmography (rPPG).

EyePreserve: Identity-Preserving Iris Synthesis

no code implementations19 Dec 2023 Siamul Karim Khan, Patrick Tinsley, Mahsa Mitcheff, Patrick Flynn, Kevin W. Bowyer, Adam Czajka

Synthesis of same-identity biometric iris images, both for existing and non-existing identities while preserving the identity across a wide range of pupil sizes, is complex due to intricate iris muscle constriction mechanism, requiring a precise model of iris non-linear texture deformations to be embedded into the synthesis pipeline.

Pupil Dilation

Iris Liveness Detection Competition (LivDet-Iris) -- The 2023 Edition

no code implementations6 Oct 2023 Patrick Tinsley, Sandip Purnapatra, Mahsa Mitcheff, Aidan Boyd, Colton Crum, Kevin Bowyer, Patrick Flynn, Stephanie Schuckers, Adam Czajka, Meiling Fang, Naser Damer, Xingyu Liu, Caiyong Wang, Xianyun Sun, Zhaohua Chang, Xinyue Li, Guangzhe Zhao, Juan Tapia, Christoph Busch, Carlos Aravena, Daniel Schulz

New elements in this fifth competition include (1) GAN-generated iris images as a category of presentation attack instruments (PAI), and (2) an evaluation of human accuracy at detecting PAI as a reference benchmark.

Promoting Generalization in Cross-Dataset Remote Photoplethysmography

no code implementations24 May 2023 Nathan Vance, Jeremy Speth, Benjamin Sporrer, Patrick Flynn

Remote Photoplethysmography (rPPG), or the remote monitoring of a subject's heart rate using a camera, has seen a shift from handcrafted techniques to deep learning models.

Full-Body Cardiovascular Sensing with Remote Photoplethysmography

no code implementations16 Mar 2023 Lu Niu, Jeremy Speth, Nathan Vance, Ben Sporrer, Adam Czajka, Patrick Flynn

In this paper we explored the feasibility of rPPG from non-face body regions such as the arms, legs, and hands.

Heart rate estimation POS

Non-Contrastive Unsupervised Learning of Physiological Signals from Video

1 code implementation CVPR 2023 Jeremy Speth, Nathan Vance, Patrick Flynn, Adam Czajka

Given the limited inductive biases and impressive empirical results, the approach is theoretically capable of discovering other periodic signals from video, enabling multiple physiological measurements without the need for ground truth signals.

Hallucinated Heartbeats: Anomaly-Aware Remote Pulse Estimation

no code implementations11 Mar 2023 Jeremy Speth, Nathan Vance, Benjamin Sporrer, Lu Niu, Patrick Flynn, Adam Czajka

Extensive experimentation with eight research datasets (rPPG-specific: DDPM, CDDPM, PURE, UBFC, ARPM; deep fakes: DFDC; face presentation attack detection: HKBU-MARs; rPPG outlier: KITTI) show better accuracy of anomaly detection for deep learning models incorporating the proposed training (75. 8%), compared to models trained regularly (73. 7%) and to hand-crafted rPPG methods (52-62%).

Anomaly Detection Face Presentation Attack Detection

Haven't I Seen You Before? Assessing Identity Leakage in Synthetic Irises

no code implementations3 Nov 2022 Patrick Tinsley, Adam Czajka, Patrick Flynn

Generative Adversarial Networks (GANs) have proven to be a preferred method of synthesizing fake images of objects, such as faces, animals, and automobiles.

Analyzing the Impact of Shape & Context on the Face Recognition Performance of Deep Networks

no code implementations5 Aug 2022 Sandipan Banerjee, Walter Scheirer, Kevin Bowyer, Patrick Flynn

In this article, we analyze how changing the underlying 3D shape of the base identity in face images can distort their overall appearance, especially from the perspective of deep face recognition.

Data Augmentation Face Recognition

Interpretable Deep Learning-Based Forensic Iris Segmentation and Recognition

1 code implementation1 Dec 2021 Andrey Kuehlkamp, Aidan Boyd, Adam Czajka, Kevin Bowyer, Patrick Flynn, Dennis Chute, Eric Benjamin

In this paper, we present an end-to-end deep learning-based method for postmortem iris segmentation and recognition with a special visualization technique intended to support forensic human examiners in their efforts.

Deep Learning Iris Recognition +2

Digital and Physical-World Attacks on Remote Pulse Detection

no code implementations21 Oct 2021 Jeremy Speth, Nathan Vance, Patrick Flynn, Kevin W. Bowyer, Adam Czajka

Remote photoplethysmography (rPPG) is a technique for estimating blood volume changes from reflected light without the need for a contact sensor.

Face Presentation Attack Detection

Deception Detection and Remote Physiological Monitoring: A Dataset and Baseline Experimental Results

no code implementations11 Jun 2021 Jeremy Speth, Nathan Vance, Adam Czajka, Kevin W. Bowyer, Diane Wright, Patrick Flynn

Our application context is an interview scenario in which the interviewee attempts to deceive the interviewer on selected responses.

Deception Detection

Remote Pulse Estimation in the Presence of Face Masks

no code implementations11 Jan 2021 Jeremy Speth, Nathan Vance, Patrick Flynn, Kevin Bowyer, Adam Czajka

Remote photoplethysmography (rPPG), a family of techniques for monitoring blood volume changes, may be especially useful for widespread contactless health monitoring using face video from consumer-grade visible-light cameras.

Data Augmentation Heart rate estimation

This Face Does Not Exist ... But It Might Be Yours! Identity Leakage in Generative Models

1 code implementation10 Dec 2020 Patrick Tinsley, Adam Czajka, Patrick Flynn

This raises privacy-related questions, but also stimulates discussions of (a) the face manifold's characteristics in the feature space and (b) how to create generative models that do not inadvertently reveal identity information of real subjects whose images were used for training.

Learning Transformation-Aware Embeddings for Image Forensics

no code implementations13 Jan 2020 Aparna Bharati, Daniel Moreira, Patrick Flynn, Anderson Rocha, Kevin Bowyer, Walter Scheirer

To establish the efficacy of the proposed approach, comparisons with state-of-the-art handcrafted and deep learning-based descriptors, and image matching approaches are made.

Image Forensics Object Recognition

Dynamic Spatial Verification for Large-Scale Object-Level Image Retrieval

no code implementations24 Mar 2019 Joel Brogan, Aparna Bharati, Daniel Moreira, Kevin Bowyer, Patrick Flynn, Anderson Rocha, Walter Scheirer

Images from social media can reflect diverse viewpoints, heated arguments, and expressions of creativity, adding new complexity to retrieval tasks.

Clustering Content-Based Image Retrieval +3

On Low-Resolution Face Recognition in the Wild: Comparisons and New Techniques

no code implementations29 May 2018 Pei Li, Loreto Prieto, Domingo Mery, Patrick Flynn

Although face recognition systems have achieved impressive performance in recent years, the low-resolution face recognition (LRFR) task remains challenging, especially when the LR faces are captured under non-ideal conditions, as is common in surveillance-based applications.

Face Identification Face Recognition +1

Face Recognition in Low Quality Images: A Survey

no code implementations29 May 2018 Pei Li, Loreto Prieto, Domingo Mery, Patrick Flynn

Its applications lie widely in the real-world environment when high-resolution or high-quality images are hard to capture.

Deblurring Face Recognition +2

Provenance Filtering for Multimedia Phylogeny

1 code implementation1 Jun 2017 Allan Pinto, Daniel Moreira, Aparna Bharati, Joel Brogan, Kevin Bowyer, Patrick Flynn, Walter Scheirer, Anderson Rocha

Departing from traditional digital forensics modeling, which seeks to analyze single objects in isolation, multimedia phylogeny analyzes the evolutionary processes that influence digital objects and collections over time.

U-Phylogeny: Undirected Provenance Graph Construction in the Wild

1 code implementation31 May 2017 Aparna Bharati, Daniel Moreira, Allan Pinto, Joel Brogan, Kevin Bowyer, Patrick Flynn, Walter Scheirer, Anderson Rocha

Deriving relationships between images and tracing back their history of modifications are at the core of Multimedia Phylogeny solutions, which aim to combat misinformation through doctored visual media.

graph construction Misinformation

To Frontalize or Not To Frontalize: Do We Really Need Elaborate Pre-processing To Improve Face Recognition?

1 code implementation16 Oct 2016 Sandipan Banerjee, Joel Brogan, Janez Krizaj, Aparna Bharati, Brandon RichardWebster, Vitomir Struc, Patrick Flynn, Walter Scheirer

If a CNN is intended to tolerate facial pose, then we face an important question: should this training data be diverse in its pose distribution, or should face images be normalized to a single pose in a pre-processing step?

Face Recognition

Hierarchical Clustering in Face Similarity Score Space

no code implementations19 May 2016 Jason Grant, Patrick Flynn

Similarity scores in face recognition represent the proximity between pairs of images as computed by a matching algorithm.

Clustering Face Recognition

Cannot find the paper you are looking for? You can Submit a new open access paper.