Three-dimensional human pose estimation from monocular video remains challenging for clinical gait analysis due to high computational cost and the need for temporal consistency. We present Pose3DM, a bidirectional Mamba-based state-space framework th...
Jump analysis in figure skating is important. Recovering the 3D pose of a figure skater has become increasingly important. However, issues such as restrictions from an athlete’s clothing, self-occlusion, abnormal pose and so on will result in p...
Optical sensor technologies are reshaping obesity detection by enabling non-invasive, dynamic analysis of biomechanical and morphological biomarkers. This review synthesizes recent advances in three key areas: optical gait analysis, vision-based pose...
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...
Two-dimensional (2D) clinical gait analysis systems are more affordable and portable than contemporary three-dimensional (3D) clinical models. Using the Vicon 3D motion capture system as the standard, we evaluated the internal statistics of the Imase...
Human pose estimation (HPE) has become a prevalent research topic in computer vision. The technology can be applied in many areas, such as video surveillance, medical assistance, and sport motion analysis. Due to higher demand for HPE, many HPE libra...
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...
The face blurring of images plays a key role in protecting privacy. However, in computer vision, especially for the human pose estimation task, machine-learning models are currently trained, validated, and tested on original datasets without face blu...
Geometric features, such as the topological and manifold properties, are utilized to extract geometric properties. Geometric methods that exploit the applications of geometrics, e.g., geometric features, are widely used in computer graphics and compu...
Pose tracking and captioning are extensively employed for motion capturing and activity description in daylight vision scenarios. Activity detection through camera systems presents a complex challenge, necessitating the refinement of numerous algorit...
Affective computing in general and human activity and intention analysis in particular comprise a rapidly-growing field of research. Head pose and emotion changes present serious challenges when applied to player’s training and ludology experience in...
Digital fitness has become a widely used tool for remote exercise guidance, leveraging artificial intelligence to analyze exercise videos and support self-training. This paper introduces a method for self-training in golf, a sport where automated pos...
Markerless human pose estimation is increasingly used for kinematic assessment, but evidence of its applicability to upper limb movements across different ranges of motion (ROM) remains limited. This study examined the accuracy and reliability of a m...
Non-rigid point cloud registration holds significant importance for human body pose analysis in the fields of sports, medicine, gaming, etc. In this paper, we propose a non-rigid point cloud registration algorithm based on geodesic distance measureme...
In sport science, athlete tracking and motion analysis are essential for monitoring and optimizing training programs, with the goal of increasing success in competition and preventing injury. At present, contact-free, camera-based, multi-athlete dete...
Cricket has a massive global following and is ranked as the second most popular sport globally, with an estimated 2.5 billion fans. Batting requires quick decisions based on ball speed, trajectory, fielder positions, etc. Recently, computer vision an...
Due to the growing interest in climbing, increasing importance has been given to research in the field of non-invasive, camera-based motion analysis. While existing work uses invasive technologies such as wearables or modified walls and holds, or foc...
Parkinson’s disease (PD) is a progressive neurodegenerative disorder that severely impacts motor function, necessitating early detection for effective management. However, current diagnostic methods are expensive and resource-intensive, limitin...
Accurate human posture classification in images and videos is crucial for automated applications across various fields, including work safety, physical rehabilitation, sports training, or daily assisted living. Recently, multimodal learning methods,...
Human activity recognition (HAR) is pivotal in advancing applications ranging from healthcare monitoring to interactive gaming. Traditional HAR systems, primarily relying on single data sources, face limitations in capturing the full spectrum of huma...
Human Pose Estimation (HPE) is a computer vision application that utilizes deep learning techniques to precisely locate Key Joint Points (KJPs), enabling the accurate description of a person’s pose. HPE models can be extended to facilitate Rang...
The research introduces a unique deep-learning-based technique for remote rehabilitative analysis of image-captured human movements and postures. We present a ploninomial Pareto-optimized deep-learning architecture for processing inverse kinematics f...
Chronic, dysregulated inflammation contributes to colitis-associated colorectal cancer (CRC), and the cGAS–STING pathway represents a central but therapeutically challenging node because both insufficient and excessive STING activity can be pat...
Abnormal movement of the head and neck is a typical symptom of Cervical Dystonia (CD). Accurate scoring on the severity scale is of great significance for treatment planning. The traditional scoring method is to use a protractor or contact sensors to...
Human Pose Recovery has been studied in the field of Computer Vision for the last 40 years. Several approaches have been reported, and significant improvements have been obtained in both data representation and model design. However, the problem of H...
The field of additive manufacturing, particularly 3D printing, has ushered in a significant transformation in the realm of joint arthritis treatment through prosthetic surgery. This innovative technology allows for the creation of bespoke prosthetic...
Over recent years, automated Human Activity Recognition (HAR) has been an area of concern for many researchers due to its widespread application in surveillance systems, healthcare environments, and many more. This has led researchers to develop cohe...
In recent years, thanks to the development of additive manufacturing techniques, pros-thetic surgery has reached increasingly cutting-edge levels, revolutionizing the clinical course of patients suffering from joint arthritis, rheumatoid arthritis, p...
This study examined the efficacy of an optimized DeepLabCut (DLC) model in motion capture, with a particular focus on the sit-to-stand (STS) movement, which is crucial for assessing the functional capacity in elderly and postoperative patients. This...
Recent advancements have made two-dimensional (2D) clinical gait analysis systems more accessible and portable than traditional three-dimensional (3D) clinical systems. This study evaluates the reliability and validity of gait measurements using mono...
Swimming performance analysis increasingly depends on multimodal sensing systems that capture physiological and biomechanical signals in real-world aquatic environments. While progress has been made in sensor fidelity and automated analysis, the inte...
Human Pose Estimation (HPE) models have varied applications and represent a cutting-edge branch of study, whose systems such as MediaPipe (MP), OpenPose (OP), and AlphaPose (ALP) show marked success. One of these areas, however, that is inadequately...
Humans learn movements naturally, but it takes a lot of time and training to achieve expert performance in motor skills. In this review, we show how modern technologies can support people in learning new motor skills. First, we introduce important co...
Motion capture systems have recently experienced a strong evolution. New cheap depth sensors and open source frameworks, such as OpenNI, allow for perceiving human motion on-line without using invasive systems. However, these proposals do not evaluat...
Marker-based 3D motion capture systems, widely used for gait analysis, are accurate but have disadvantages such as cost and accessibility. Whereas markerless pose estimation has emerged as a convenient and cost-effective alternative for gait analysis...
The assessment of running kinematics is essential for injury prevention and rehabilitation, including anterior cruciate ligament sprains. Recent advances in computer vision have enabled the development of tools for quantifying kinematics in research...
Expressive imitation in the performing arts is typically trained through animal behavior imitation, aiming not only to reproduce action trajectories but also to recreate rhythm, style and emotional states. However, evaluation of such animal imitation...
The emergence of various types of commercial cameras (compact, high resolution, high angle of view, high speed, and high dynamic range, etc.) has contributed significantly to the understanding of human activities. By taking advantage of the character...
Accuracy validation of gait analysis using pose estimation with artificial intelligence (AI) remains inadequate, particularly in objective assessments of absolute error and similarity of waveform patterns. This study aimed to clarify objective measur...
Parkinson’s disease (PD) is the second most common movement disorder in the world. It is characterized by motor and non-motor symptoms that have a profound impact on the independence and quality of life of people affected by the disease, which...
Rapid pose classification and pose retrieval in 3D human datasets are important problems in shape analysis. In this paper, we extend the Multi-View Convolutional Neural Network (MVCNN) with ordered view feature fusion for orientation-aware 3D human p...
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...
Human pose recognition is a new field of study that promises to have widespread practical applications. While there have been efforts to improve human position estimation with radio frequency identification (RFID), no major research has addressed the...
Three-dimensional (3D) pose estimation has been widely used in many three-dimensional human motion analysis applications, where inertia-based path estimation is gradually being adopted. Systems based on commercial inertial measurement units (IMUs) us...
Industrial exoskeletons (a.k.a. wearable robots) have been developed to reduce musculoskeletal fatigue and work injuries. Human joint kinematics and human–robot alignment are important measurements in understanding the effects of industrial exo...
Gait analysis plays an important role in the fields of healthcare and sports sciences. Conventional gait analysis relies on costly equipment such as optical motion capture cameras and wearable sensors, some of which require trained assessors for data...
Sleep healthcare at home is a new research topic that needs to develop new sensors, hardware and algorithms with the consideration of convenience, portability and accuracy. Monitoring sleep behaviors by visual sensors represents one new unobtrusive a...
This paper addresses the problem of accurate and robust tracking of 3D human body pose from depth image sequences. Recovering the large number of degrees of freedom in human body movements from a depth image sequence is challenging due to the need to...
Three-dimensional human pose estimation has made significant advancements through the integration of deep learning techniques. This survey provides a comprehensive review of recent 3D human pose estimation methods, with a focus on monocular images, v...
Although modeling self-attention can significantly reduce computational complexity, human pose estimation performance is still affected by occlusion and background noise, and undifferentiated feature fusion leads to significant information loss. To a...
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