One motivation for studying semi-supervised techniques for human pose estimation is to compensate for the lack of variety in curated 3D human pose datasets by combining labeled 3D pose data with readily available unlabeled video data—effectivel...
Axial postural abnormalities (aPA) are common features of Parkinson’s disease (PD) and manifest in over 20% of patients during the course of the disease. aPA form a spectrum of functional trunk misalignment, ranging from a typical Parkinsonian...
Recently, posture recognition technology has advanced rapidly. Herein, we present a novel posture angle calculation system utilizing a single inertial measurement unit and a spatial geometric equation to accurately identify the three-dimensional (3D)...
Force-based human posture estimation (FPE) provides a valuable alternative when camera-based human motion capturing is impractical. It offers new opportunities for sensor integration in smart products for patient monitoring, ergonomic optimization an...
Running posture estimation is a specialized task in human pose estimation that has received relatively little research attention due to the lack of appropriate datasets. To address this issue, this paper presents the construction of a new benchmark d...
This paper suggests that human pose estimation (HPE) and sustainable event classification (SEC) require an advanced human skeleton and context-aware features extraction approach along with machine learning classification methods to recognize daily ev...
Event-based sensors provide sparse, motion-centric measurements that can reduce data bandwidth and enable always-on perception on resource-constrained edge devices. This paper presents an event-based machine vision framework for smart-home AIoT that...
The spinal angle is an important indicator of body balance. It is important to restore the 3D shape of the human body and estimate the spine center line. Existing multi-image-based body restoration methods require expensive equipment and complex proc...
In contrast to the physical activities of able-bodied people at home, most people who require long-term specific care (e.g., bedridden patients and patients who have difficulty walking) usually show more low-intensity slow physical activities with po...
This paper presents a novel, accessible pipeline for the prediction and prevention of motion-related joint injuries in multiple individuals. Current methodologies for biomechanical analysis often rely on complex, restrictive setups such as multi-came...
Estimating human posture in crowded smart teaching environments is a fundamental technical challenge for measuring learners’ engagement levels. This work presents a model for detecting critical points in human posture using ECAv2-HRNet in crowded sit...
In response to the numerous challenges faced by traditional human pose recognition methods in practical applications, such as dense targets, severe edge occlusion, limited application scenarios, complex backgrounds, and poor recognition accuracy when...
This paper proposes an action recognition algorithm based on the capsule network and Kalman filter called “Reading Pictures Instead of Looking” (RPIL). This method resolves the convolutional neural network’s over sensitivity to rotation and scaling a...
This paper presents a human-in-the-loop interactive framework for skeleton-based posture recognition, designed to support model training and artistic education. A total of 4870 labeled images are used for training and validation, and 500 images are r...
Posture, defined as the body’s alignment relative to gravity, plays a vital role in musculoskeletal health by influencing muscle efficiency, joint integrity, and overall balance. The global shift to remote and sedentary work environments during...
Robots and artificial intelligence have revolutionized the healthcare sector. Transporting patients within hospitals is critical; however, reducing errors and inefficiencies caused by human intervention and increasing task efficiency are necessary. T...
Robots and artificial intelligence have revolutionized the healthcare sector. Patient transportation within hospitals is emerging as a critical application; however, reducing errors and inefficiencies caused by human intervention and ensuring safe, e...
Human pose estimation has a variety of real-life applications, including human action recognition, AI-powered personal trainers, robotics, motion capture and augmented reality, gaming, and video surveillance. However, most current human pose estimati...
9 August 2022
Musculoskeletal disorders are an unavoidable occupational health problem. In particular, workers who perform repetitive tasks onsite in the manufacturing industry suffer from musculoskeletal problems. In this paper, we propose a system that evaluates...
Wearing safety harness is essential for workers when carrying out work. When posture of the workers in the workshop is complex, using real-time detection program to detect workers wearing safety harness is challenging, with a high false alarm rate. I...
Current methods for ergonomic assessment often use video-analysis to estimate wrist postures during occupational tasks. Wearable sensing and machine learning have the potential to automate this tedious task, and in doing so greatly extend the amount...
Advances in video capturing devices enable adaptive posture estimation (APE) and event classification of multiple human-based videos for smart systems. Accurate event classification and adaptive posture estimation are still challenging domains, altho...
Human motion retrieval and analysis is a useful means of activity recognition to 3D human bodies. An efficient method is proposed to estimate human motion by using symmetric joint points and limb features of various limb parts based on regression tas...
This paper presents a mathematical model that can be used to virtually reconstruct the posture of the human spine. By using orientation angles from a wearable monitoring system based on inertial sensors, the model calculates and represents the curvat...
Ergonomics is important for smooth and sustainable industrial operation. In the manufacturing industry, due to poor workstation design, workers frequently and repeatedly experience uncomfortable postures and actions (reaching above their shoulders, b...
With the rapid technological advancements in wearable devices, motion and health management have significantly improved, enabling the measurement of various biometric data with compact equipment. Our research focuses on motion measurement but, in gen...
This study constructed an integrated underwater pipeline monitoring system, which combines pipeline posture sensing modules and pipeline leakage detection modules. The proposed system can achieve the real-time monitoring of pipeline posture and the c...
Posture recognition has been widely applied in fields such as physical training, environmental awareness, human-computer-interaction, surveillance system and elderly health care. The traditional methods consist of two main variations: machine vision...
For many applications (e.g., surveillance and disaster response), situational awareness is essential. In these applications, human body posture recognition in real time plays a crucial role for corresponding response. Traditional posture recognition...
This study addresses the challenges of human–robot interactions in real-time environments with adaptive field-programmable gate array (FPGA)-based accelerators. Predicting human posture in indoor environments in confined areas is a significant...
Indoor device-free localization (DFL) systems are used in various Internet-of-Things applications based on human behavior recognition. However, the usage of camera-based intuitive DFL approaches is limited in dark environments and disaster situations...
As the manipulation object of a patient transfer robot is a human, which can be considered a complex and time-varying system, motion adjustment of a patient transfer robot is inevitable and essential for ensuring patient safety and comfort. This pape...
This paper presents a novel approach to address the problem of increasing the number of parameters in existing human posture estimation network models while trying to improve prediction accuracy. We propose a human posture estimation optimization net...
The elderly are constantly in danger of falling and injuring themselves without anyone realizing it. A safety-monitoring system based on microwaves can ease these concerns. The authors have proposed safety-monitoring systems that use multiple-input m...
A custom HW design of a Fully Convolutional Neural Network (FCN) is presented in this paper to implement an embeddable Human Posture Recognition (HPR) system capable of very high accuracy both for laying and sitting posture recognition. The FCN explo...
Human detection is the task of locating all instances of human beings present in an image, which has a wide range of applications across various fields, including search and rescue, surveillance, and autonomous driving. The rapid advancement of compu...
Human activity recognition (HAR) has been increasingly used in medical care, behavior analysis, and entertainment industry to improve the experience of users. Most of the existing works use fixed models to identify various activities. However, they d...
Pose estimation is crucial for ensuring passenger safety and better user experiences in semi- and fully autonomous vehicles. Traditional methods relying on pose estimation from regular color images face significant challenges due to a lack of three-d...
Human pose estimation is an important research direction in the field of computer vision, which aims to accurately identify the position and posture of keypoints of the human body through images or videos. However, multi-person pose estimation yields...
Pose estimation plays a crucial role in recognizing and analyzing the postures, actions, and movements of humans and animals using computer vision and machine learning techniques. However, bird pose estimation encounters specific challenges, includin...
Billions of people are using smartphones and computers with poor posture. A careless attitude towards spinal posture could be dangerous for long-term spinal health, leading eventually to curvature of the spine. Ignoring this fact and its treatment at...
Detecting posture changes of athletes in sports is an important task in teaching and training competitions, but its detection remains challenging due to the diversity and complexity of sports postures. This paper introduces a single-stage pose estima...
Accurate motion capture plays an important role in sports analysis, the medical field and virtual reality. Current methods for motion capture often suffer from occlusions, which limits the accuracy of their pose estimation. In this paper, we propose...
Posture analysis is important in musculoskeletal disorder prevention but relies on subjective assessment. This study investigates the applicability and reliability of a machine learning (ML) pose estimation model for the human posture assessment, whi...
Three-dimensional human pose estimation is widely applied in sports, robotics, and healthcare. In the past five years, the number of CNN-based studies for 3D human pose estimation has been numerous and has yielded impressive results. However, studies...
The monitoring of head posture is crucial for interactive learning, in order to build feedback with learners’ attention, especially in the explosion of digital teaching that occurred during the current COVID-19 pandemic. However, conventional m...
In this work, we present a multiclass hand posture classifier useful for human-robot interaction tasks. The proposed system is based exclusively on visual sensors, and it achieves a real-time performance, whilst detecting and recognizing an alphabet...
Utilizing tactile sensors embedded in intelligent mats is an attractive non-intrusive approach for human motion analysis. Interpreting tactile pressure 2D maps for accurate posture estimation poses significant challenges, such as dealing with data sp...
Relating continuously collected inertial data to the activities or postures performed by the sensor wearer requires pattern recognition or machine-learning-based algorithms, accounting for the temporal and scale variability present in human movements...
A video-based method to quantify animal posture movement is a powerful way to analyze animal behavior. Both humans and fish can judge the physiological state through the skeleton framework. However, it is challenging for farmers to judge the breeding...
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