High-frequency surface wave radar (HFSWR) can detect and continuously track ship objects in real time and beyond the horizon. When ships navigate in a sea area, their motions in a time period form a scenario. The diversity and complexity of the motio...
Recognition and understanding of ship motion patterns have excellent application value for ship navigation and maritime supervision, i.e., route planning and maritime risk assessment. This paper proposes a semantic recognition method for ship motion...
Assessing task workload during military En Route Critical Care (ERCC) and other high-risk clinical operations remains challenging. This study evaluated heart rate variability (HRV) and body motion as digital biomarkers of task workload among Critical...
Background/Objectives: Motion artifacts significantly distort fluorescence measurements during surgical perfusion assessment, potentially leading to incorrect clinical decisions. This study evaluates the efficacy of automated motion compensation (MC)...
Pre-defined motion command profiles enable precise positioning and dynamic control in mechanical and mechatronic systems, maximizing efficiency and reliability. Real-world applications introduce dynamic factors like mechanical compliance, friction, a...
To address the challenges posed by traditional tracking algorithms in adapting to complex underwater environments characterized by nonlinear motion, drastic morphological changes, mimicry camouflage, and frequent occlusions in wild Chinese giant sala...
Conventional multi-object tracking approaches frequently exhibit performance degradation in marine radar (MR) imagery due to complex environmental challenges. To overcome these limitations, this paper proposes ShipMOT, an innovative multi-object trac...
Accurate and robust drone detection is an important and challenging task. However, on this issue, previous research, whether based on appearance or motion features, has not yet provided a satisfactory solution, especially under a complex background....
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...
UAV-based video multi-object tracking (MOT) is a significant task in the field of remote sensing. However, current research still faces critical issues: (1) the limitations of the single architecture of DNNs inherently hinder performance improvement...
In the context of this research work, we studied the problem of privacy preserving on spatiotemporal databases. In particular, we investigated the k-anonymity of mobile users based on real trajectory data. The k-anonymity set consists of the k neares...
Micro-electromechanical system (MEMS) micromirrors have been in development for many years, but the ability to steer beams to angles larger than 20° remains a challenging endeavor. This paper details a MEMS micromirror device capable of achieving lar...
Dynamic myocardial CT perfusion imaging enables functional assessment of coronary artery stenosis and myocardial microvascular disease. However, it is susceptible to residual motion artifacts arising from cardiac and respiratory activity. These artif...
Gait instability is critical in medicine and healthcare, as it has associations with balance disorder and physical impairment. With the development of sensor technology, despite the fact that numerous wearable gait detection and recognition systems h...
This paper presents a comparison of mathematical and cinematic motion analysis regarding the accuracy of the detection of alterations in the patterns of positional sequence during biceps-curl lifting exercise. Two different methods, one with and one...
Twenty-one experienced runners completed three treadmill running sessions on different days. Each session consisted of three consecutive 2 min trials at self-selected speeds (RPE = 3, 5, and 7). An eight-camera marker-less motion capture system and i...
Color remote sensing images have key features of pronounced internal similarity characterized by numerous repetitive local patterns, so the capacity to effectively harness these self-similarity features plays a key role in the enhancement of color im...
Digital image correlation (DIC) is widely used in material experiments such as ores; the quality of a speckle image directly affects the accuracy of the DIC calculation. This study aims to acquire high-quality speckle pattern images and improve the c...
Diagnosing cervical spine instability with flexion-extension radiographs is challenging, as current guidelines are based on limited cadaver studies and do not adequately account for level, vertebral size, or patient effort. There is a need for automa...
Extended object tracking is crucial for autonomous driving, as it enables vehicles to perceive and respond to their environment accurately by considering an object’s shape, size, and motion over time. Two commonly used methods for extended obje...
A brane-world metric with an external magnetic field is a modified theory of gravity. It is suitable for the description of compact sources on the brane such as stars and black holes. We design a class of explicit symplectic integrators for this spac...
Tropical cyclone (TC) track clustering plays a crucial role in understanding cyclone movement patterns, which is essential for risk assessment and disaster preparedness. This study proposes an improved SD-K-Means clustering algorithm for classifying...
Brain magnetic resonance imaging (MRI) is highly susceptible to motion artifacts that degrade fine structural details and undermine quantitative analysis. Conventional U-Net-based deep learning approaches for motion artifact reduction typically opera...
Robust and accurate attitude and heading estimation using Micro-Electromechanical System (MEMS) Inertial Measurement Units (IMU) is the most crucial technique that determines the accuracy of various downstream applications, especially pedestrian dead...
The Segment Anything Model 2 (SAM2) has achieved state-of-the-art performance in pixel-level object segmentation for both static and dynamic visual content. Its streaming memory architecture maintains spatial context across video sequences, yet strug...
The increasing prevalence of cognitive disorders among the elderly is a significant consequence of the global aging phenomenon. Wandering stands out as the most prominent and challenging symptom in these patients, with potential irreversible conseque...
Interpersonal synchrony is a time-dependent coordination pattern in which interacting partners’ body movements become temporally aligned. This study frames interpersonal synchrony as a human motion analysis problem and presents Synchrony Vision...
This study presents the design and experimental testing of a two-degrees-of-freedom (2DOF) elbow prosthesis prototype designed to replicate the movement patterns of a native or normal human elbow. Two methods of the control of the prosthesis, namely,...
This paper proposes a Dynamic Flow Spatio-Temporal Generative Adversarial Network (DFST-GAN) model for high-quality precipitation nowcasting. Current spatio-temporal prediction models struggle with two key limitations: the inability to adaptively cap...
Unmanned surface vehicle (USV)’s motion is represented by time-series data that exhibit highly nonlinear and non-stationary features, significantly influenced by environmental factors, such as wind speed and waves, when sailing on the sea. The...
Accurate golf swing correction requires modeling not only static pose deviations but also temporal rhythm and biomechanical stability throughout the swing sequence. Most existing pose-based approaches rely on frame-wise similarity and therefore fail...
Additive manufacturing enables the development of low-cost, self-built robotic systems; however, their performance is typically not characterized by validated metrics. The paper presents a photogrammetric concept intended for system-independent appli...
Recent systems for position and movement monitoring are increasingly enhanced by the integration of advanced AI techniques. Besides traditional analytical and algorithmic approaches, which are still applied in areas such as signal processing, sensor...
Globally, cigarette smoking is widespread among all ages, and smokers struggle to quit. The design of effective cessation interventions requires an accurate and objective assessment of smoking frequency and smoke exposure metrics. Recently, wearable...
Structural traits of vegetation, derived from the three-dimensional distribution of plant elements, are closely linked to ecosystem functions such as productivity and habitat provision. While extensively studied in forest ecosystems, these traits rem...
Inclusive design does not stop at removing physical obstacles such as staircases. It also involves identifying architectural features that impose sensory burdens, such as repetitive visual patterns that are known to potentially cause dizziness or vis...
Remotely operated vehicles (ROVs) equipped with multibeam forward-looking sonar are widely used for underwater object search in environments where visibility is limited. Ensuring complete three-dimensional (3D) scan coverage within a bounded mission...
In marine surveillance, distinguishing between normal and anomalous vessel movement patterns is critical for identifying potential threats in a timely manner. Once detected, it is important to monitor and track these vessels until a necessary interve...
This paper evaluates the current maturity of automatic code-generation workflows for deploying modern CNN-based object detectors on embedded GPU platforms. We compare a native pipeline against a code generation pipeline through a Model-Based Engineer...
In addressing the challenges of trajectory prediction in multi-ship interaction scenarios and aiming to improve the accuracy of multi-ship trajectory prediction, this paper proposes a multi-ship trajectory prediction model, GL-STGCNN. The GL-STGCNN m...
Vehicle tracking is essential for autonomous driving, traffic surveillance, and intelligent transportation, yet most existing trackers rely on frame-level training that neglects temporal dependencies. This mismatch between training and testing leads...
Computed Tomography (CT) is a widely used imaging modality that employs X-rays and computational reconstruction to visualize internal anatomy. Although higher radiation doses produce higher-quality images, they also increase long-term cancer risk, mo...
Background/Objectives: Nonverbal synchrony—the temporal coordination of physical behaviors such as head movement and gesture—is a critical component of effective social communication. Individuals with autism spectrum disorder (ASD) are of...
Posture, physical activity, and sleep have been shown to be linked to many health issues but are difficult to assess in laboratories, especially in terms of long-term patterns. Worn on the body, inertial measurement units (IMUs) measure motion and ha...
Environmental perception plays an essential role in autonomous driving tasks and demands robustness in cluttered dynamic environments such as complex urban scenarios. In this paper, a robust Multiple Object Detection and Tracking (MODT) algorithm for...
Predicting pedestrian trajectories in urban scenarios is a challenging task that has a wide range of applications, from video surveillance to autonomous driving. The task is difficult since pedestrian behavior is affected by both their individual pat...
Generally, accurate gait analysis plays a vital role in assessing neurological disorders, human walking patterns, fall risk predictions, etc. In this work, a deep learning framework was implemented using three different deep learning models for gait...
Kinematics data are primary biomechanical parameters. A principal component analysis (PCA) of waveforms is a statistical approach used to explore patterns of variability in biomechanical curve datasets. Differences in experienced and recreational run...
Motion sickness (MS) is a prevalent condition that can significantly degrade user comfort and immersion, particularly in virtual reality (VR) environments. Accurate prediction models are essential for early detection and mitigation of MS symptoms, th...
Small, forested catchments are prototypes of terrestrial ecosystems and have been studied in several disciplines of environmental science over several decades. Time series of water and matter fluxes and nutrient concentrations from these systems exhi...
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