Radargrammetry is a useful approach to generate Digital Surface Models (DSMs) and an alternative to InSAR techniques that are subject to temporal or atmospheric decorrelation. Stereo image matching in radargrammetry refers to the process of determini...
Semi-Global Matching (SGM) approximates a 2D Markov Random Field (MRF) via multiple 1D scanline optimizations, which serves as a good trade-off between accuracy and efficiency in dense matching. Nevertheless, the performance is limited due to the sim...
Measuring speed is a critical factor to reduce motion artifacts for dynamic scene capture. Phase-shifting methods have the advantage of providing high-accuracy and dense 3D point clouds, but the phase unwrapping process affects the measurement speed....
High efficiency and accuracy of semi-global matching (SGM) make it widely used in many stereo vision applications. However, SGM not only struggles in dealing with pixels in homogeneous area, but also suffers from streak artifacts. In this paper, we p...
As the core issue for Digital Surface Model (DSM) generation, image matching is often implemented in photo space to get disparity or depth map. However, DSM is generated in object space with additional processes such as reference image selection, dis...
Automatic charging for electric vehicles has broad development prospects for meeting the personalized service experience of users while overcoming the inherent safety hazards. An identification and positioning approach suitable for engineering applic...
The low light conditions, abundant dust, and rocky terrain on the lunar surface pose challenges for scientific research. To effectively perceive the surrounding environment, lunar rovers are equipped with binocular cameras. In this paper, with the ai...
With FaSS-MVS, we present a fast, surface-aware semi-global optimization approach for multi-view stereo that allows for rapid depth and normal map estimation from monocular aerial video data captured by unmanned aerial vehicles (UAVs). The data estim...
Graph Neural Networks (GNNs) have gained popularity in image matching methods, proving useful for various computer vision tasks like Structure from Motion (SfM) and 3D reconstruction. A well-known example is SuperGlue. Lightweight variants, such as L...
Image-text matching is a crucial aspect of multi-modal intelligence. The main challenge in this area is accurately measuring the relevance between the image and text, using evidence obtained through matching. Previous studies either concentrated on o...
Robust and accurate face alignment remains a challenging task, especially when local noises, illumination variations and partial occlusions exist in images. The existing local search and global match methods often misalign due to local optima without...
The integration of deep learning with optical flow estimation in Particle Image Velocimetry (PIV) represents an emerging solution. Extensive research indicates that deep learning has potential to match or outperform state-of-the-art classical algorit...
Vision-based underwater autonomous systems play a significant role in marine exploration. Stereo matching is one of the most popular applications for vision-based underwater autonomous systems, which recovers the geometric information of underwater s...
This paper presents a novel image matching method for multi-source satellite images, which integrates global Shuttle Radar Topography Mission (SRTM) data and image segmentation to achieve robust and numerous correspondences. This method first generat...
Semi-global matching (SGM) has been widely used in binocular vision. In spite of its good efficiency, SGM still has difficulties in dealing with low-texture regions. In this paper, an SGM algorithm based on multi-scale information fusion (MSIF), name...
Due to the great success of convolutional neural networks (CNNs) in the area of computer vision, the existing methods tend to match the global or local CNN features between images for near-duplicate image detection. However, global CNN features are n...
The performance of unsupervised stereo matching in complex regions such as weak textures and occlusions is constrained by the inherently local receptive fields of convolutional neural networks (CNNs), the absence of geometric priors, and the limited...
Robust and accurate line segment matching remains a critical challenge in stereo vision, particularly in space-based applications where weak texture, structural symmetry, and strong illumination variations are common. This paper presents a multi-cons...
We propose a novel approach, GMIW-Pose, to estimate the relative camera poses between two views. This method leverages a Transformer-based global matching module to obtain robust 2D–2D dense correspondences, followed by iterative refinement of...
This study aims to comprehensively analyze five weather forecasting models obtained from the Open-Meteo historical data repository, with a specific emphasis on evaluating their impact in predicting wind power generation. Given the increasing focus on...
Feature matching is to detect and match corresponding feature points in stereo pairs, which is one of the key techniques in accurate camera orientations. However, several factors limit the feature matching accuracy, e.g., image textures, viewing angl...
The generation of Digital Elevation Models (DEMs) through stereogrammetry of optical satellite images has gained great popularity across various disciplines. For the analysis of these DEMs, it is important to understand the influence of the input dat...
A novel nonlinear dynamic modeling approach is proposed for the T-shaped beam structures widely used in the field of aerospace. All of the geometrical nonlinearities including the terms in the deformation of the beams, the terms at the connections, a...
Multi-modal remote sensing image (MRSI) matching suffers from severe nonlinear radiometric distortions and geometric deformations, and conventional feature-based techniques are generally ineffective. This study proposes a novel and robust MRSI matchi...
Place recognition is widely used to re-localize robots in pre-built point cloud maps for navigation. However, current place recognition methods can only be used to recognize previously visited places. Moreover, these methods are limited by the requir...
As the largest source of uncertainty in carbon cycle studies, accurate quantification of gross primary productivity (GPP) is critical for the global carbon budget in the context of global climate change. Numerous vegetation indices (VIs) based on sat...
Wearable and smartphone technology innovations have propelled the growth of Pedestrian Navigation Services (PNS). PNS need a map-matching process to project a user’s locations onto maps. Many map-matching techniques have been developed for vehicle na...
Multi-Target Multi-Camera Tracking (MTMCT), which aims to track multiple targets within a multi-camera network, has recently attracted considerable attention due to its wide range of applications. The main challenge of MTMCT is to match local trackle...
Accurate and robust camera pose estimation is essential for high-level applications such as augmented reality and autonomous driving. Despite the development of global feature-based camera pose regression methods and local feature-based matching guid...
Global motion greatly increases the number of false alarms for object detection in video sequences against dynamic backgrounds. Therefore, before detecting the target in the dynamic background, it is necessary to estimate and compensate the global mo...
The matching degree between agricultural water and land resources directly determines the sustainable development of regional agriculture. Based on climate data corrected by delta statistical downscaling from five global climate models (GCMs) in the...
Visual/Inertial/GNSS (VIG) integrated navigation and positioning systems are widely used in unmanned vehicles and other systems. This VIG system is vulnerable to of GNSS spoofing attacks. Relevant research on the harm that spoofing causes to the syst...
This study aimed to quantify the external match loads (EMLs) of a Portuguese u-23 soccer team, competing at the highest national level for the age group, comparing players with different starting status throughout a competitive season and specific bl...
Binocular stereoscopic matching is an essential method in computer vision, imitating human binocular technology to obtain distance information. Among plentiful stereo matching algorithms, Semi-Global Matching (SGM) is recognized as one of the most po...
In Holoscopic imaging, a single aperture is used to acquire full-colour spatial images like a fly’s eye by gently altering angles between nearby lenses with a micro-lens array. Due to its simple data collection and visualisation methods, which...
Conventional projection systems typically require a fixed spatial configuration relative to the projection surface, with strict control over distance and angle. In contrast, UAV-mounted projectors overcome these constraints, enabling dynamic, large-s...
To better solve the problem of target detection in marine environment and to deal with the difficulty of 3D reconstruction of underwater target, a binocular vision-based underwater target detection and 3D reconstruction system is proposed in this pap...
Illumination in the natural environment is uncontrollable, and the field background is complex and changeable which all leads to the poor quality of broccoli seedling images. The colors of weeds and broccoli seedlings are close, especially under weed...
(1) Background: with the emergence and continuous development of more multinational corporations, capital and resources flow rapidly in the form of global supply chains around the world. Furthermore, government subsidies for R&D are one of the ke...
In this study, an approach using ground control point-free unmanned aerial vehicle (UAV)-based photogrammetry is proposed to estimate the volume of stockpiles carried on barges in a dynamic environment. Compared with similar studies regarding UAVs, a...
Vehicle positioning is a key factor for numerous information and assistance applications that are included in vehicles and for which satellite positioning is mainly used. However, this positioning process can result in errors and lead to measurement...
High-precision and robust localization in GNSS-denied areas is crucial for autonomous vehicles and robots. Most state-of-the-art localization methods are based on simultaneous localization and mapping (SLAM) with a camera or light detection and rangi...
This paper presents a novel method to enhance ground truth disparity maps generated by Semi-Global Matching (SGM) using Maximum a Posteriori (MAP) estimation. SGM, while not producing visually appealing outputs like neural networks, offers high dispa...
Automated three-dimensional plant phenotyping is an essential tool for non-destructive analysis of plant growth and structure. This paper presents a low-cost system based on stereo vision for depth estimation and morphological characterization of mai...
As an important part of industrial 3D scanning, a relocation algorithm is used to restore the position and the pose of a 3D scanner or to perform closed-loop detection. The real time and the relocation correct ratio are prominent and difficult points...
A computational model that can accurately describe the thermodynamics of a hydrocarbon system and its properties under various conditions is a prerequisite for running reservoir and pipeline simulations. Cubic Equations of State (EoS) are mathematica...
In this study, we use Pléiades tri-stereo data to generate a digital elevation model (DEM) from the Pléiades images using a workflow employing semi-global matching (SGM). We examine the DEM accuracy in complex mountain glaciated terrain...
With the emergence of low-cost robotic systems, such as unmanned aerial vehicle, the importance of embedded high-performance image processing has increased. For a long time, FPGAs were the only processing hardware that were capable of high-performanc...
Digital Surface Model (DSM) is a three-dimensional model presenting the elevation of the Earth’s surface, which can be obtained by the along-track or cross-track stereo images of optical satellites. This paper investigates the DSM extraction me...
With the rapid development of autonomous vehicles and intelligent transportation systems, vehicle detection and distance estimation have become critical technologies for ensuring driving safety. However, real-world in-vehicle environments impose stri...
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