Daniel Leightley

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Recent works on human action recognition have focused on representing and classifying articulated body motion. These methods require a detailed knowledge of the action composition both in the spatial and temporal domains, which is a difficult task, most notably under real-time conditions. As such, there has been a recent shift towards the exemplar paradigm(More)
The recognition of human activity is a challenging topic for machine learning. We present an analysis of Support Vector Machines (SVM) and Random Forests (RF) in their ability to accurately classify Kinect kinematic activities. Twenty participants were captured using the Microsoft Kinect performing ten physical rehabilitation activities. We extracted the(More)
There is a clear advantage to developing automated systems to detect human motion in the field of computer vision for applications associated with healthcare. We have compiled a diverse dataset of clinically-relevant motions using the Microsoft Kinect One sensor and release the dataset to the community as an open source solution for benchmarking detection,(More)
This paper aims to investigate whether micro-facial movement sequences can be distinguished from neutral face sequences. As a micro-facial movement tends to be very quick and subtle, classifying when a movement occurs compared to the face without movement can be a challenging computer vision problem. Using local binary patterns on three orthogonal planes(More)
We present the development of a virtual trainer for use by physiotherapists and patients in exercise based physiotherapy programmes. It allows a therapist to tailor exercise requirements to the specific needs and challenges of individual patients. Patients can select different programmes and follow a coach avatar to perform recorded exercises based on their(More)
Analysis and quantification of human motion to support clinicians in the decision-making process is the desired outcome for many clinical-based approaches. However, generating statistical models that are free from human interpretation and yet representative is a difficult task. In this paper, we propose a framework that automatically recognizes and(More)
Evaluating the execution style of human motion can give insight into the performance and behaviour exhibited by the participant. This could enable support in developing personalised rehabilitation programmes by providing better understanding of motion mechanics and contextual behaviour. However, performing analyses, generating statistical representations(More)
The aim of this study was to compare postural sway during a series of static balancing tasks and during five chair rises between healthy young (mean [SEM], age 26 [1] years), healthy old (age 67 [1] years) and master athlete runners (age 67 [1] years; competing and training for the previous 51 [5] years) using the Microsoft Kinect One. The healthy old had(More)
Patients requiring physical rehabilitation, such as those suffering long-term chronic disease or recovering from illness or injury are reliant upon rehabilitation programmes to recover. Tele-rehabilitation has been proposed as a promising development to remove physical barriers of locality and place rehabilitation services within the patients home. We(More)