Results 51 to 60 of about 2,295 (204)
Validation of two-dimensional video-based inference of finger kinematics with pose estimation.
PLoS ONE, 2022 Accurate capture finger of movements for biomechanical assessments has typically been achieved within laboratory environments through the use of physical markers attached to a participant's hands.
Letizia Gionfrida +3 more
doaj +1 more source
Intelligent Performance Evaluation in Rowing Sport Using a Graph-Matching Network
Journal of Imaging, 2023 Rowing competitions require consistent rowing strokes among crew members to achieve optimal performance. However, existing motion analysis techniques often rely on wearable sensors, leading to challenges in sporter inconvenience.
Chien-Chang Chen +5 more
doaj +1 more source
Integrating multimodal data and machine learning for entrepreneurship research
Strategic Entrepreneurship Journal, EarlyView.Abstract Research Summary Extant research in neuroscience suggests that human perception is multimodal in nature—we model the world integrating diverse data sources such as sound, images, taste, and smell. Working in a dynamic environment, entrepreneurs are expected to draw on multimodal inputs in their decision making.
Yash Raj Shrestha, Vivianna Fang He
wiley +1 more source
OpenPose based Smoking Gesture Recognition System using Artificial Neural Network
Tehnički Glasnik, 2023 Smoking is an extremely important health problem in modern society. This study focuses on a method for preventing smoking in non-smoking areas, such as public places, as well as the development of an artificial neural network based smoking motion ...
Tae-Yeong Jeong, Il-Kyu Ha
doaj +1 more source
British Journal of Psychology, EarlyView.Abstract Adopting physical expressions of emotion has feedback effects on individuals' mood and behaviour; for example, adopting the expansive and contractive body language of dominance and submission can affect individuals' feelings of power. However, postural feedback paradigms almost exclusively use deliberate, active posture manipulations, which ...
Soren Wainio‐Theberge, Jorge Armony
wiley +1 more source
A multi-modal detection method for holding ladders in underground climbing operations
Gong-kuang zidonghuaCurrently, most research on recognizing unsafe behaviors of underground personnel focuses on improving precision through computer vision. However, underground areas are prone to occlusion, unstable lighting, and reflection, making it difficult to ...
SUN Qing, YANG Chaoyu
doaj +1 more source
Synthesising 2D Video from 3D Motion Data for Machine Learning Applications
Sensors, 2022 To increase the utility of legacy, gold-standard, three-dimensional (3D) motion capture datasets for computer vision-based machine learning applications, this study proposed and validated a method to synthesise two-dimensional (2D) video image frames ...
Marion Mundt +7 more
doaj +1 more source
Telerehabilitation System Based on OpenPose and 3D Reconstruction with Monocular Camera
Journal of Robotics and Mechatronics, 2023 Owing to aging populations, the number of elderly people with limb dysfunction affecting their daily lives will continue to increase. These populations have a great need for rehabilitation training to restore limb functions. However, the current numbers of rehabilitation hospitals and doctors are limited.
Keisuke Osawa +6 more
openaire +1 more source
Machine learning approaches in automated infant General Movements Assessment: A scoping review
Developmental Medicine &Child Neurology, EarlyView.Automated infant General Movements Assessment increasingly uses machine‐ and deep‐learning approaches to classify movement patterns and estimate cerebral palsy risk from video or sensor data. This scoping review highlights how dataset characteristics, recording environment, pose‐estimation accuracy, feature extraction, and model design influence system
Manpreet Kaur +4 more
wiley +1 more source
Types of anomalies during gait using OpenPose.
, 2023 The left panel shows the OpenPose skeletal model and the name of each part. The right panel shows the anomaly types corresponding to those in Table 1. Estimation accuracy in Table 1 is excluded from the figure for convenience of illustration.
Yusuke Matsui (2047393) +2 more
core +1 more source