266 citations · 697 across the 30 of their papers we have counts for
25 papers · 1 filter
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…
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…
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…
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…
The CSIRO Crown-of-Thorn Starfish Detection Dataset
Jiajun Liu, Brano Kusy, Ross Marchant +17
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 underway in an attemp…
In-Bed Human Pose Estimation from Unseen and Privacy-Preserving Image Domains
Ting Cao, Mohammad Ali Armin, Simon Denman +2
Medical applications have benefited greatly from the rapid advancement in computer vision. Considering patient monitoring in particular, in-bed human posture estimation offers impo…
Video-Based Inpatient Fall Risk Assessment: A Case Study
Ziqing Wang, Mohammad Ali Armin, Simon Denman +2
Inpatient falls are a serious safety issue in hospitals and healthcare facilities. Recent advances in video analytics for patient monitoring provide a non-intrusive avenue to reduc…