266 citations · 697 across the 30 of their papers we have counts for
33 papers
TADP: Dual-Branch Temporally Adaptive Differential Privacy for Expression-Aware Video Anonymization
Feng Xu, Xun Li, Lars Petersson +3
We present TADP, a temporally adaptive differential privacy (DP) framework for inference-time privacy-preserving video generation under fixed-length clip-replacement adjacency. TAD…
Navigating human-robot interaction challenges in private and residential aged care homes
David Ahmedt-Aristizabal, Mohammad Ali Armin, Akila Pemasiri +4
This chapter explores how robotic systems and ambient intelligence can enhance care for older adults in residential aged care (RAC) homes and private homes. Although these settings…
InfoTaxa: Information-Calibrated Label-Free Clustering for Fine-Grained Visual Taxonomy
David Ahmedt-Aristizabal, Mohammad Ali Armin, Lars Petersson
Label-free clustering of frozen pretrained visual embeddings offers a scalable route to biodiversity monitoring, but image-only fine-grained taxonomy exhibits a consistent coarse-t…
Knowledge Priors for Identity-Disentangled Open-Set Privacy-Preserving Video FER
Feng Xu, Xun Li, Lars Petersson +3
Facial expression recognition relies on facial data that inherently expose identity and thus raise significant privacy concerns. Current privacy-preserving methods typically fail i…
Non-Invasive 3D Wound Measurement with RGB-D Imaging
Lena Harkämper, Leo Lebrat, David Ahmedt-Aristizabal +3
Chronic wound monitoring and management require accurate and efficient wound measurement methods. This paper presents a fast, non-invasive 3D wound measurement algorithm based on R…
Multi-View Consistent Wound Segmentation With Neural Fields
Remi Chierchia, Léo Lebrat, David Ahmedt-Aristizabal +4
Wound care is often challenged by the economic and logistical burdens that consistently afflict patients and hospitals worldwide. In recent decades, healthcare professionals have s…
Facial Spatiotemporal Graphs: Leveraging the 3D Facial Surface for Remote Physiological Measurement
Sam Cantrill, David Ahmedt-Aristizabal, Lars Petersson +2
Facial remote photoplethysmography (rPPG) methods estimate physiological signals by modeling subtle color changes on the 3D facial surface over time. However, existing methods fail…
Wound3DAssist: A Practical Framework for 3D Wound Assessment
Remi Chierchia, Rodrigo Santa Cruz, Léo Lebrat +7
Managing chronic wounds remains a major healthcare challenge, with clinical assessment often relying on subjective and time-consuming manual documentation methods. Although 2D digi…
Facial Expression Recognition with Controlled Privacy Preservation and Feature Compensation
Feng Xu, David Ahmedt-Aristizabal, Lars Petersson +2
Facial expression recognition (FER) systems raise significant privacy concerns due to the potential exposure of sensitive identity information. This paper presents a study on remov…
Developing Normative Gait Cycle Parameters for Clinical Analysis Using Human Pose Estimation
Rahm Ranjan, David Ahmedt-Aristizabal, Mohammad Ali Armin +1
Gait analysis using computer vision is an emerging field in AI, offering clinicians an objective, multi-feature approach to analyse complex movements. Despite its promise, current…
Computer Vision for Clinical Gait Analysis: A Gait Abnormality Video Dataset
Rahm Ranjan, David Ahmedt-Aristizabal, Mohammad Ali Armin +1
Clinical gait analysis (CGA) using computer vision is an emerging field in artificial intelligence that faces barriers of accessible, real-world data, and clear task objectives. Th…
SALVE: A 3D Reconstruction Benchmark of Wounds from Consumer-grade Videos
Remi Chierchia, Leo Lebrat, David Ahmedt-Aristizabal +3
Managing chronic wounds is a global challenge that can be alleviated by the adoption of automatic systems for clinical wound assessment from consumer-grade videos. While 2D image a…
NeRF Director: Revisiting View Selection in Neural Volume Rendering
Wenhui Xiao, Rodrigo Santa Cruz, David Ahmedt-Aristizabal +3
Neural Rendering representations have significantly contributed to the field of 3D computer vision. Given their potential, considerable efforts have been invested to improve their…
Orientation-conditioned Facial Texture Mapping for Video-based Facial Remote Photoplethysmography Estimation
Sam Cantrill, David Ahmedt-Aristizabal, Lars Petersson +2
Camera-based remote photoplethysmography (rPPG) enables contactless measurement of important physiological signals such as pulse rate (PR). However, dynamic and unconstrained subje…
Backpropagation-free Network for 3D Test-time Adaptation
Yanshuo Wang, Ali Cheraghian, Zeeshan Hayder +7
Real-world systems often encounter new data over time, which leads to experiencing target domain shifts. Existing Test-Time Adaptation (TTA) methods tend to apply computationally h…
Deep Learning Approaches for Seizure Video Analysis: A Review
David Ahmedt-Aristizabal, Mohammad Ali Armin, Zeeshan Hayder +5
Seizure events can manifest as transient disruptions in the control of movements which may be organized in distinct behavioral sequences, accompanied or not by other observable fea…
Continual Test-time Domain Adaptation via Dynamic Sample Selection
Yanshuo Wang, Jie Hong, Ali Cheraghian +4
The objective of Continual Test-time Domain Adaptation (CTDA) is to gradually adapt a pre-trained model to a sequence of target domains without accessing the source data. This pape…
Syn3DWound: A Synthetic Dataset for 3D Wound Bed Analysis
Léo Lebrat, Rodrigo Santa Cruz, Remi Chierchia +12
Wound management poses a significant challenge, particularly for bedridden patients and the elderly. Accurate diagnostic and healing monitoring can significantly benefit from moder…
Automated Coronary Arteries Labeling Via Geometric Deep Learning
Yadan Li, Mohammad Ali Armin, Simon Denman +1
Automatic labelling of anatomical structures, such as coronary arteries, is critical for diagnosis, yet existing (non-deep learning) methods are limited by a reliance on prior topo…
Vision-Based Activity Recognition in Children with Autism-Related Behaviors
Pengbo Wei, David Ahmedt-Aristizabal, Harshala Gammulle +2
Advances in machine learning and contactless sensors have enabled the understanding complex human behaviors in a healthcare setting. In particular, several deep learning systems ha…
A Real-time Edge-AI System for Reef Surveys
Yang Li, Jiajun Liu, Brano Kusy +12
Crown-of-Thorn Starfish (COTS) outbreaks are a major cause of coral loss on the Great Barrier Reef (GBR) and substantial surveillance and control programs are ongoing to manage COT…
Monitoring of Pigmented Skin Lesions Using 3D Whole Body Imaging
David Ahmedt-Aristizabal, Chuong Nguyen, Lachlan Tychsen-Smith +5
Advanced artificial intelligence and machine learning have great potential to redefine how skin lesions are detected, mapped, tracked and documented. Here, We propose a 3D whole-bo…
Continuous Human Action Recognition for Human-Machine Interaction: A Review
Harshala Gammulle, David Ahmedt-Aristizabal, Simon Denman +3
With advances in data-driven machine learning research, a wide variety of prediction models have been proposed to capture spatio-temporal features for the analysis of video streams…
Privacy-Preserving In-Bed Pose Monitoring: A Fusion and Reconstruction Study
Thisun Dayarathna, Thamidu Muthukumarana, Yasiru Rathnayaka +4
Recently, in-bed human pose estimation has attracted the interest of researchers due to its relevance to a wide range of healthcare applications. Compared to the general problem of…