10 citations · 22 across the 10 of their papers we have counts for
12 papers
Self-Supervised Animal Identification for Long Videos
Xuyang Fang, Sion Hannuna, Edwin Simpson +1
Identifying individual animals in long-duration videos is essential for behavioral ecology, wildlife monitoring, and livestock management. Traditional methods require extensive man…
8-Calves Image dataset
Xuyang Fang, Sion Hannuna, Neill Campbell +1
Automated livestock monitoring is crucial for precision farming, but robust computer vision models are hindered by a lack of datasets reflecting real-world group challenges. We int…
Universal Bovine Identification via Depth Data and Deep Metric Learning
Asheesh Sharma, Lucy Randewich, William Andrew +7
This paper proposes and evaluates, for the first time, a top-down (dorsal view), depth-only deep learning system for accurately identifying individual cattle and provides associate…
VI-Net: View-Invariant Quality of Human Movement Assessment
Faegheh Sardari, Adeline Paiement, Sion Hannuna +1
We propose a view-invariant method towards the assessment of the quality of human movements which does not rely on skeleton data. Our end-to-end convolutional neural network consis…
Towards automated mobile-phone-based plant pathology management
Nantheera Anantrasirichai, Sion Hannuna, Nishan Canagarajah
This paper presents a framework which uses computer vision algorithms to standardise images and analyse them for identifying crop diseases automatically. The tools are created to b…
CaloriNet: From silhouettes to calorie estimation in private environments
Alessandro Masullo, Tilo Burghardt, Dima Damen +3
We propose a novel deep fusion architecture, CaloriNet, for the online estimation of energy expenditure for free living monitoring in private environments, where RGB data is discar…
Semantically Selective Augmentation for Deep Compact Person Re-Identification
Víctor Ponce-López, Tilo Burghardt, Sion Hannunna +3
We present a deep person re-identification approach that combines semantically selective, deep data augmentation with clustering-based network compression to generate high performa…
A Guide to the SPHERE 100 Homes Study Dataset
Atis Elsts, Tilo Burghardt, Dallan Byrne +18
The SPHERE project has developed a multi-modal sensor platform for health and behavior monitoring in residential environments. So far, the SPHERE platform has been deployed for dat…
Automatic Leaf Extraction from Outdoor Images
N. Anantrasirichai, Sion Hannuna, Nishan Canagarajah
Automatic plant recognition and disease analysis may be streamlined by an image of a complete, isolated leaf as an initial input. Segmenting leaves from natural images is a hard pr…
Calorie Counter: RGB-Depth Visual Estimation of Energy Expenditure at Home
Lili Tao, Tilo Burghardt, Majid Mirmehdi +6
We present a new framework for vision-based estimation of calorific expenditure from RGB-D data - the first that is validated on physical gas exchange measurements and applied to d…
Multiple Human Tracking in RGB-D Data: A Survey
Massimo Camplani, Adeline Paiement, Majid Mirmehdi +4
Multiple human tracking (MHT) is a fundamental task in many computer vision applications. Appearance-based approaches, primarily formulated on RGB data, are constrained and affecte…
The SPHERE Challenge: Activity Recognition with Multimodal Sensor Data
Niall Twomey, Tom Diethe, Meelis Kull +8
This paper outlines the Sensor Platform for HEalthcare in Residential Environment (SPHERE) project and details the SPHERE challenge that will take place in conjunction with Europea…