143 citations · 796 across the 22 of their papers we have counts for
22 papers
Pain level and pain-related behaviour classification using GRU-based sparsely-connected RNNs
Mohammad Mahdi Dehshibi, Temitayo Olugbade, Fernando Diaz-de-Maria +2
There is a growing body of studies on applying deep learning to biometrics analysis. Certain circumstances, however, could impair the objective measures and accuracy of the propose…
Self-adversarial Multi-scale Contrastive Learning for Semantic Segmentation of Thermal Facial Images
Jitesh Joshi, Nadia Bianchi-Berthouze, Youngjun Cho
Segmentation of thermal facial images is a challenging task. This is because facial features often lack salience due to high-dynamic thermal range scenes and occlusion issues. Limi…
Learn2Agree: Fitting with Multiple Annotators without Objective Ground Truth
Chongyang Wang, Yuan Gao, Chenyou Fan +4
The annotation of domain experts is important for some medical applications where the objective ground truth is ambiguous to define, e.g., the rehabilitation for some chronic disea…
Bridging the gap between emotion and joint action
M. M. N. Bieńkiewicz, A. Smykovskyi, T. Olugbade +5
Our daily human life is filled with a myriad of joint action moments, be it children playing, adults working together (i.e., team sports), or strangers navigating through a crowd.…
Leveraging Activity Recognition to Enable Protective Behavior Detection in Continuous Data
Chongyang Wang, Yuan Gao, Akhil Mathur +3
Protective behavior exhibited by people with chronic pain (CP) during physical activities is the key to understanding their physical and emotional states. Existing automatic protec…
Libri-Adapt: A New Speech Dataset for Unsupervised Domain Adaptation
Akhil Mathur, Fahim Kawsar, Nadia Berthouze +1
This paper introduces a new dataset, Libri-Adapt, to support unsupervised domain adaptation research on speech recognition models. Built on top of the LibriSpeech corpus, Libri-Ada…
Mic2Mic: Using Cycle-Consistent Generative Adversarial Networks to Overcome Microphone Variability in Speech Systems
Akhil Mathur, Anton Isopoussu, Fahim Kawsar +2
Mobile and embedded devices are increasingly using microphones and audio-based computational models to infer user context. A major challenge in building systems that combine audio…
Evaluating Saliency Map Explanations for Convolutional Neural Networks: A User Study
Ahmed Alqaraawi, Martin Schuessler, Philipp Weiß +2
Convolutional neural networks (CNNs) offer great machine learning performance over a range of applications, but their operation is hard to interpret, even for experts. Various expl…
Multimodal Data Fusion based on the Global Workspace Theory
Cong Bao, Zafeirios Fountas, Temitayo Olugbade +1
We propose a novel neural network architecture, named the Global Workspace Network (GWN), which addresses the challenge of dynamic and unspecified uncertainties in multimodal data…
EMOPAIN Challenge 2020: Multimodal Pain Evaluation from Facial and Bodily Expressions
Joy O. Egede, Siyang Song, Temitayo A. Olugbade +7
The EmoPain 2020 Challenge is the first international competition aimed at creating a uniform platform for the comparison of machine learning and multimedia processing methods of a…
Physiological and Affective Computing through Thermal Imaging: A Survey
Youngjun Cho, Nadia Bianchi-Berthouze
Thermal imaging-based physiological and affective computing is an emerging research area enabling technologies to monitor our bodily functions and understand psychological and affe…
Nose Heat: Exploring Stress-induced Nasal Thermal Variability through Mobile Thermal Imaging
Youngjun Cho, Nadia Bianchi-Berthouze, Manuel Oliveira +2
Automatically monitoring and quantifying stress-induced thermal dynamic information in real-world settings is an extremely important but challenging problem. In this paper, we expl…
Learning Bodily and Temporal Attention in Protective Movement Behavior Detection
Chongyang Wang, Min Peng, Temitayo A. Olugbade +3
For people with chronic pain, the assessment of protective behavior during physical functioning is essential to understand their subjective pain-related experiences (e.g., fear and…
Chronic-Pain Protective Behavior Detection with Deep Learning
Chongyang Wang, Temitayo A. Olugbade, Akhil Mathur +3
In chronic pain rehabilitation, physiotherapists adapt physical activity to patients' performance based on their expression of protective behavior, gradually exposing them to feare…
Instant Automated Inference of Perceived Mental Stress through Smartphone PPG and Thermal Imaging
Youngjun Cho, Simon J. Julier, Nadia Bianchi-Berthouze
Background: A smartphone is a promising tool for daily cardiovascular measurement and mental stress monitoring. A smartphone camera-based PhotoPlethysmoGraphy (PPG) and a low-cost…
Automatic Detection of Reflective Thinking in Mathematical Problem Solving based on Unconstrained Bodily Exploration
Temitayo A. Olugbade, Joseph Newbold, Rose Johnson +6
For technology (like serious games) that aims to deliver interactive learning, it is important to address relevant mental experiences such as reflective thinking during problem sol…
Deep Thermal Imaging: Proximate Material Type Recognition in the Wild through Deep Learning of Spatial Surface Temperature Patterns
Youngjun Cho, Nadia Bianchi-Berthouze, Nicolai Marquardt +1
We introduce Deep Thermal Imaging, a new approach for close-range automatic recognition of materials to enhance the understanding of people and ubiquitous technologies of their pro…
RealPen: Providing Realism in Handwriting Tasks on Touch Surfaces using Auditory-Tactile Feedback
Youngjun Cho, Andrea Bianchi, Nicolai Marquardt +1
We present RealPen, an augmented stylus for capacitive tablet screens that recreates the physical sensation of writing on paper with a pencil, ball-point pen or marker pen. The aim…
ThermSense: Smartphone-based Breathing Sensing Platform using Noncontact Low-Cost Thermal Camera
Youngjun Cho, Nadia Bianchi-Berthouze, Simon J. Julier +1
The ability of sensing breathing is becoming an increasingly important function for technology that aims at supporting both psychological and physical wellbeing. We demonstrate The…
DeepBreath: Deep Learning of Breathing Patterns for Automatic Stress Recognition using Low-Cost Thermal Imaging in Unconstrained Settings
Youngjun Cho, Nadia Bianchi-Berthouze, Simon J. Julier
We propose DeepBreath, a deep learning model which automatically recognises people's psychological stress level (mental overload) from their breathing patterns. Using a low cost th…
Robust tracking of respiratory rate in high-dynamic range scenes using mobile thermal imaging
Youngjun Cho, Simon J. Julier, Nicolai Marquardt +1
The ability to monitor respiratory rate is extremely important for medical treatment, healthcare and fitness sectors. In many situations, mobile methods, which allow users to under…
Believing in BERT: Using expressive communication to enhance trust and counteract operational error in physical Human-Robot Interaction
Adriana Hamacher, Nadia Bianchi-Berthouze, Anthony G. Pipe +1
Strategies are necessary to mitigate the impact of unexpected behavior in collaborative robotics, and research to develop solutions is lacking. Our aim here was to explore the bene…