Accurate measurement of the 6-DOF motion responses of marine floating structures is essential for structural safety assessment and operational decision-making. To address the critical issues of integration drift in inertial navigation systems, suscep...
Advanced sensor signal analysis is increasingly important for intelligent health management in human-centered environments, where continuous perception and real-time interpretation of motion-related signals are essential for safe and adaptive assista...
Traditional limb kinematic analysis relies on manual goniometer measurements. With computer vision advancements, integrating RGB cameras can minimize manual labor. Although deep learning-based cameras aim to offer the same ease as manual goniometers,...
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...
Computer vision is a subcategory of artificial intelligence focused on extraction of information from images and video. It provides a compelling new means for objective orthopaedic gait assessment in horses using accessible hardware, such as a smartp...
This study aimed to develop a monocular vision-based tennis serve analysis system and evaluate its effectiveness in beginner training. The system uses MediaPipe Pose to extract 33 body landmarks from monocular video, calculates joint angles using thr...
Dynamic objects present a major challenge for visual simultaneous localization and mapping (Visual SLAM), as feature measurements originating from moving regions can corrupt camera pose estimation and lead to inaccurate maps. In this paper, we propos...
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...
This study validates a clinically accessible approach for quantifying the Upper Extremity Reachable Workspace (UERW) using monocular AI-driven Markerless Motion Capture (MMC). Objective validation of such techniques for clinically oriented tasks is e...
Human motion capture is crucial for various fields, but traditional optical systems (OMC) are costly and restrictive. Monocular video-based methods offer accessibility, yet face accuracy challenges, especially in dynamic sports like tennis. This stud...
Pedestrian flow statistics and analysis in public places is an important means to ensure urban safety. However, in recent years, a video-based pedestrian flow statistics algorithm mainly relies on binocular vision or a vertical downward camera, which...
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...
Techniques for measuring the position and orientation of an object from corresponding images are based on the principles of epipolar geometry in the computer vision and photogrammetric fields. Contributing to their importance, many different approach...
Human pose estimation refers to the estimation of the location of body parts and how they are connected in an image. Human pose estimation from monocular images has wide applications (e.g., image indexing). Several surveys on human pose estimation ca...
Curling requires precise sweeping to control both the speed and trajectory of a stone, making quantitative analysis of sweeping behavior an important challenge for performance evaluation and tactical support. However, existing curling studies have pr...
In recent years, significant research has been conducted on video-based human pose estimation (HPE). While monocular two-dimensional (2D) HPE has been shown to achieve high performance, monocular three-dimensional (3D) HPE poses a more challenging pr...
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...
As a fundamental and challenging problem, non-rigid structure-from-motion (NRSfM) has attracted a large amount of research interest. It is worth mentioning that NRSfM has been applied to dynamic scene understanding and motion segmentation. Especially...
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...
Work-related musculoskeletal disorders (WMSDs) represent a significant health challenge for workers in construction environments, often arising from prolonged exposure to ergonomic risks associated with manual labor, awkward postures, and repetitive...
Collaborative simultaneous localization and mapping have a great impact on various applications such as search-and-rescue and agriculture. For each agent, the key to performing collaboration is to measure the motion relative to other participants or...
Pure monocular 3D reconstruction is a complex problem that has attracted the research community’s interest due to the affordability and availability of RGB sensors. SLAM, VO, and SFM are disciplines formulated to solve the 3D reconstruction pro...
In the rapidly evolving field of computer vision and machine learning, 3D skeleton estimation is critical for applications such as motion analysis and human–computer interaction. While stereo cameras are commonly used to acquire 3D skeletal dat...
The composition or bed material plays a crucial role in the physical hydromorphological processes of fluvial systems. However, conventional bed material sampling methods provide only pointwise information, which can be inadequate when investigating l...
The integration of artificial intelligence into video-based human behavior analysis enables contactless and continuous monitoring of both motor dynamics and facial reactions. This paper proposes a dual-stream multimodal framework for synchronized mod...
Traditional biomechanical analysis is constrained by high capital costs and the physical limitations imposed by markers, posing significant barriers to clinical adoption. This review evaluates the emergence of artificial intelligence (AI)-based marke...
Plantar load is an important biomechanical measure in gait analysis, rehabilitation assessment, and human movement evaluation. However, conventional measurement systems, including instrumented insoles and laboratory-based force measurement devices, r...
Online multi-object tracking (MOT) has broad applications in time-critical video analysis scenarios such as advanced driver-assistance systems (ADASs) and autonomous driving. In this paper, the proposed system aims at tracking multiple vehicles in th...
The exploration of remote, unknown, rough environments by autonomous robots strongly depends on the ability of the on-board system to build an accurate predictor of terrain traversability. Terrain traversability prediction can be made more cost effic...
Handball performance analysis is still often conducted through the manual review of match videos, while automation on broadcast footage remains challenging due to camera motion, strong perspective effects, and frequent occlusions during dense interac...
Precise and real-time acquisition of aircraft model attitude is fundamental for aerodynamic analysis in wind tunnel experiments, yet achieving high-precision non-contact measurement remains a significant challenge. To address this, this paper propose...
Road defect detection is essential for traffic safety and infrastructure maintenance. Excising automated methods based on 2D image analysis lack spatial context and cannot provide accurate 3D localization required for maintenance planning. We propose...
Clinical gait analysis plays a central role in the rehabilitation of stroke patients. However, practical and technical challenges limit their use in clinical settings. This study aimed to validate SMARTGAIT, a deep learning-based gait analysis system...
The integration of AI vision-based sensing and human motion analysis has grown to be a key element of intelligent perception systems, which now allow for automated interpretation of human movement, activity patterns, and complex visual behaviors. How...
Robotic handling of objects is not always a trivial assignment, even in teleoperation where, in most cases, this might lead to stressful labor for operators. To reduce the task difficulty, supervised motions could be performed in safe scenarios to re...
In recent years, artificial intelligence (AI) has significantly impacted agricultural operations, particularly with the development of deep learning models for animal monitoring and farming automation. This study focuses on evaluating the Depth Anyth...
This paper presents SE2-LET-VINS, an enhanced Visual–Inertial Simultaneous Localization and Mapping (VI-SLAM) system built upon the classic Visual–Inertial Navigation System for Monocular Cameras (VINS-Mono) framework, designed to improve...
Off-road navigation in forest environments is a challenging problem in field robotics. Rovers are required to infer their traversability over a priori unknown and dynamically changing forest terrain using noisy onboard navigation sensors. The problem...
This paper presents a vision-guided nonlinear model predictive control (MPC) framework for coordinated dual-manipulator pre-contact acquisition of tumbling targets. Temporal monocular estimation supplies pose, motion, and uncertainty; rigid-body pred...
Autonomous driving systems rely on a sophisticated pipeline of artificial intelligence models to perceive, predict, and plan in dynamic environments. This review presents a systematic analysis of the machine learning and deep learning models underpin...
This paper develops a theoretical framework and a numerical implementation for real-time estimation of the gross mass of heavy vehicles using only on-board signals: tire inflation pressure from the TPMS and radial deformation inferred from a monocula...
This paper presents a novel approach for estimating 3D human pose from monocular video sequences in underwater scenarios, tackling the unique challenges posed by water refraction, body occlusion, low image quality and illumination distortion in under...
Visual ecology explores how animal visual systems are related to light environments and important visual tasks. Anolis is a species-rich genus of small lizards that rely extensively on vision. Different species occupy habitats with different vegetati...
Three-dimensional (3D) reconstruction using images is one of the most significant topics in computer vision and photogrammetry, with wide-ranging applications in robotics, augmented reality, and mapping. This study investigates methods of 3D reconstr...
Objective: Functional training exercises involve complex multi-joint movements that challenge traditional rule-based or data-driven recognition systems. This paper introduces a Movement Description Language (MDL) designed to formally represent, analy...
Ammonia nitrogen is one of the most common environmental stressors in aquaculture water environments, and its accumulation can induce physiological disturbance, altered ventilation regulation, and abnormal behavioral responses in fish. To achieve non...
Rapid developments in the field of underwater photogrammetry have given scientists the ability to produce accurate 3-dimensional (3D) models which are now increasingly used in the representation and study of local areas of interest. This paper addres...
To achieve non-contact and continuous monitoring of body length in Micropterus salmoides and overcome the stress damage and subjective error associated with traditional manual measurement, this paper proposes an improved YOLOv8-based multi-target tra...
In recent years, the rapid development of unmanned aerial vehicle (UAV) technologies has made data acquisition increasingly convenient, and three-dimensional (3D) reconstruction has emerged as a popular subject of research in this context. These 3D m...