Aiming at the problem of the low accuracy of projector calibration in a structured light system, an improved projector calibration method is proposed in this paper. One of the key ideas is to estimate the sub-pixel coordinates in the projector image...
When performing linear fitting on datasets containing outliers, common algorithms may face problems like inadequate fitting accuracy. We propose a linear fitting algorithm based on Locality-Sensitive Hashing (LSH) and Random Sample Consensus (RANSAC)...
This paper presents a new method of removing mismatches of redundant points based on oriented fast and rotated brief (ORB) in vision simultaneous localization and mapping (SLAM) systems. On the one hand, the grid-based motion statistics (GMS) algorit...
A common problem with matching algorithms, in photogrammetry and computer vision, is the imperfection of finding all correct corresponding points, so-called inliers, and, thus, resulting in incorrect or mismatched points, so-called outliers. Many alg...
Determining samples is considered to be a precondition in deep network training and learning, but at present, samples are usually created manually, which limits the application of deep networks. Therefore, this article proposes an OpenStreetMap (OSM)...
Many classic visual monocular SLAM (simultaneous localization and mapping) systems have been developed over the past decades, yet most of them fail when dynamic scenarios dominate. DM-SLAM is proposed for handling dynamic objects in environments base...
Vanishing point detection is a fundamental step in computer vision that allows 3D scene understanding and autonomous navigation. Classical techniques have significant challenges when trying to understand scenes that are heavily cluttered and images c...
Compared to traditional rough casting grinding (RCG), the individualization of castings is very different, which makes it difficult to realize the automation of casting grinding. At this stage, the primary method is manual grinding. In this study, th...
The exact location of objects, such as infrastructure, is crucial to the systematic understanding of the built environment. The emergence and development of the Internet of Things (IoT) have attracted growing attention to the low-cost location scheme...
Feature point matching is a fundamental task in computer vision such as vision simultaneous localization and mapping (VSLAM) and structure from motion (SFM). Due to the similarity or interference of features, mismatches are often unavoidable. Therefo...
The accurate and efficient segmentation of large-scale urban point clouds is crucial for many higher-level tasks, such as boundary line extraction, point cloud registration, and deformation measurement. In this paper, we propose a novel supervoxel se...
It is a great challenge for a safe surgery to localize the cutting tip during laminar grinding. To address this problem, we develop a framework of state estimation based on the CT image–force model. For the proposed framework, the pre-operative...
Carrier-based Unmanned Aerial Vehicle (CUAV) landing is an extremely critical link in the overall chain of CUAV operations on ships. Vision-based landing location methods have advantages such as low cost and high accuracy. However, when an aircraft c...
This paper proposes a stereo-vision-based method that detects and registers the positions and postures of muti-type, randomly placed miniature circuit breaker (MCB) components within scene point clouds acquired by a 3D stereo camera. The method is de...
This study proposes a 3D global localization method that implements mobile LiDAR mapping and point cloud registration to recognize the locations of objects in an underground mine. An initial global point cloud map was built for an entire underground...
Fisheye cameras are widely used in visual localization due to the advantage of the wide field of view. However, the severe distortion in fisheye images lead to feature matching difficulties. This paper proposes an IMU-assisted fisheye image matching...
This paper presents a multi-session monocular Simultaneous Localization and Mapping (SLAM) approach focused on underwater environments. The system is composed of three main blocks: a visual odometer, a loop detector, and an optimizer. Single session...
To encourage the use of hydrogen energy and improve the dependability of hydrogen fuel cells, this study develops a two-stage semi-supervised framework for anomaly pattern discovery and codification. Isolation Forest, One-Class Support Vector Machine...
There are a variety of land cover products generated from remote-sensing images. However, misclassification errors in individual products and inconsistency among them undermine their utilities for research and other applications. While it is worth de...
Tactile sensors, because of their intrinsic insensitivity to lighting conditions and water turbidity, provide promising opportunities for augmenting the capabilities of vision sensors in applications involving object recognition and localization. Thi...
Prompt optimization through textual feedback has shown promising results in improving the performance of large language models (LLMs) on downstream tasks. However, existing approaches often rely on selecting prompt edits from a pool of candidate grad...
Robust and effective fruit detection and localization is essential for robotic harvesting systems. While extensive research efforts have been devoted to improving fruit detection, less emphasis has been placed on the fruit localization aspect, which...
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...
This paper presents a monocular visual odometry algorithm that incorporates a wheeled vehicle model for ground vehicles. The main innovation of this algorithm is to use the single-track bicycle model to interpret the relationship between the yaw rate...
The autonomous positioning of tunneling equipment is the key to intellectualization and robotization of a tunneling face. In this paper, a method based on simultaneous localization and mapping (SLAM) to estimate the body pose of a roadheader and buil...
Aiming at the insufficient accuracy and accumulated error of the point cloud registration of LiDAR-inertial odometry (LIO) in an urban environment, we propose a LiDAR-inertial-GNSS fusion positioning algorithm based on voxelized accurate registration...
With the growing demand for precise absolute pose estimation of landers in lunar exploration missions, crater database-based navigation technology has become a core path to achieving this goal, but it faces challenges of low efficiency in large-scale...
We address the problem of aerial image geolocalization over an area as large as a whole city through road network matching, which is modeled as a 2D point set registration problem under the 2D projective transformation and solved in a two-stage manne...
To address the challenges in large-scale packaging and printing workshops, where the dense arrangement of electromechanical equipment leads to large-scale scenes and prominent repetitive structures, and where frequent dynamic disturbances impair the...
Visual localization, i.e., the camera pose localization within a known three-dimensional (3D) model, is a basic component for numerous applications such as autonomous driving cars and augmented reality systems. The most widely used methods from the l...
Ground filtering is necessary in processing airborne light detection and ranging (LiDAR) point clouds for forestry applications. This study proposes a progressive plane detection filtering (PPDF) method. First, the method uses multi-scale planes to c...
The Nyquist folding receiver (NYFR) can achieve a high-probability interception of an ultra-wideband (UWB) signal with fewer devices, while the output of the NYFR is converted into a hybrid modulated signal of the local oscillator (LO) and the receiv...
A simultaneous localization and mapping (SLAM) algorithm allows a mobile robot or a driverless car to determine its location in an unknown and dynamic environment where it is placed, and simultaneously allows it to build a consistent map of that envi...
To address the high-precision navigation requirements of urban low-altitude electric vertical take-off and landing (eVTOL) aircraft in environments where global navigation satellite systems (GNSSs) are denied and under complex urban terrain condition...
Feature matching is a fundamental procedure in several image processing methods applied in remote sensing. Multispectral sensors with different wavelengths can provide complementary information. In this work, we propose a multispectral line segment m...
The important problem of Simultaneous Localization and Mapping (SLAM) in dynamic environments is less studied than the counterpart problem in static settings. In this paper, we present a solution for the feature-based SLAM problem in dynamic environm...
Compressive sensing in the ambiguity domain facilitates high-performance reconstruction of time-frequency distributions (TFDs) for non-stationary signals. However, identifying the optimal regularization parameter in the absence of prior knowledge rem...
Background/Objectives: Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are a frequent cause of emergency room (ER) visits, yet assessment, treatment, and discharge processes may lack standardization. This initiative aimed to ide...
To address the challenges of dynamic obstacles, limited perception, and multi-UAV coordination constraints in complex urban environments, a hierarchical control framework based on a virtual leader-follower architecture is proposed, covering global pl...
Automatically and accurately reconstructing the overhead wires of railway from airborne laser scanning (ALS) data are an efficient way of railway monitoring to ensure stable and safety transportation services. However, due to the complex structure of...
Using a single sensor to determine the pose estimation of a device cannot give accurate results. This paper presents a fusion of an inertial sensor of six degrees of freedom (6-DoF) which comprises the 3-axis of an accelerometer and the 3-axis of a g...
Multi-label text feature selection aims to identify compact and discriminative feature subsets for documents associated with multiple correlated labels. In federated environments, this task is further complicated by high-dimensional search spaces, no...
Machine learning (ML) has shown its effectiveness in handling multi-geoinformation. Yet, the black-box nature of ML algorithms has restricted their widespread adoption in the domain of mineral prospectivity mapping (MPM). In this paper, methods for i...
Point cloud registration is the foundation and key step for many vital applications, such as digital city, autonomous driving, passive positioning, and navigation. The difference of spatial objects and the structure complexity of object surfaces are...
The smooth area on the rail surface causes abnormal exposure in the laser section image, resulting in measurement errors of the rail profile. To address this issue, a novel rail profile measurement technique based on polarization fusion imaging is pr...
An improved approach for the measurement of the relative pose between a target and a chaser spacecraft is presented. The selected method is based on a single camera, which can be mounted on the chaser, and a plurality of fiducial markers, which can b...
Rollers, integral to road construction, are undergoing rapid advancements in unmanned functionality. To address the specific challenge of unmanned compaction within tunnels, we propose a vision-based odometry system for unmanned rollers. This system...
Imagery registration is a fundamental step, which greatly affects later processes in image mosaic, multi-spectral image fusion, digital surface modelling, etc., where the final solution needs blending of pixel information from more than one images. I...
No-reference image quality assessment (NR-IQA) metrics are widely used to evaluate and train image and video processing algorithms, but the growing reliance on deep neural networks makes these metrics vulnerable to adversarial attacks. Among such att...
To address the issue of significant point cloud ghosting in the construction of high-precision point cloud maps by low-speed intelligent mobile vehicles due to the presence of numerous dynamic obstacles in the environment, which affects the accuracy...
of 2