Error estimation and adaptive applications help to control the discretization errors in finite element analysis. The study implements the radial point interpolation (RPI)-based error-recovery approaches in finite element analysis. The displacement/pr...
In this paper, we propose two novel AR glasses pose estimation algorithms from single infrared images by using 3D point clouds as an intermediate representation. Our first approach “PointsToRotation” is based on a Deep Neural Network alone, whereas o...
Absolute orientation estimation is one of the key steps in computer vision, and n 2D–3D point correspondences can be used to obtain the absolute orientation, which is known as the perspective-n-point problem (PnP). The lowest number of point co...
Panel data of our interest consist of a moderate number of panels, while the panels contain a small number of observations. An estimator of common breaks in panel means without a boundary issue for this kind of scenario is proposed. In particular, th...
This article presents a new approach for obtaining the change point in the hazard function. The proposed approach is developed with the Bayesian estimator. Using a simulation study, mean value and mean square error (MSE) of proposed estimator are obt...
Aiming at tracking sharply maneuvering targets, this paper develops novel variational adaptive state estimators for joint target state and process noise parameter estimation for a class of linear state-space models with abruptly changing parameters....
The effect of geological modeling largely depends on the normal estimation results of geological sampling points. However, due to the sparse and uneven characteristics of geological sampling points, the results of normal estimation have great uncerta...
Gesture interaction allows users to interact with objects through natural hand movements without direct physical contact. However, in gesture interaction, the hand moves frequently with large variations in direction, and hand joints are prone to self...
A basic question in computational geometry is how to find the relationship between a set of points and a line in a real plane. In this paper, we present multidimensional data structures for N points that allow answering the following queries for any...
This paper presents a robust point cloud registration method based on a multi-scale covariance matrix descriptor and an accurate transformation estimation. Compared with state-of-the-art feature descriptors, such as FPH, 3DSC, spin image, etc., our p...
Lower limb knee–ankle prostheses can effectively assist above-knee amputees in completing their basic daily activities. This study explored methods for estimating the joint kinematics of intelligent lower limb prostheses to better adapt them to...
With the increasing capacity of renewable energy sources, uncertainties regarding renewable energy and other dynamic loads in integrated energy systems (IESs) are increasing. Thus, it is necessary to study the probabilistic energy flow (PEF) of IESs....
Pallet pose estimation is one of the key technologies for automated fork pickup of driverless industrial trucks. Due to the complex working environment and the enormous amount of data, the existing pose estimation approaches cannot meet the working r...
Functional size measures are widely used for estimating software development effort. After the introduction of Function Points, a few “simplified” measures have been proposed, aiming to make measurement simpler and applicable when fully d...
This work presents a localization scheme for use in wireless sensor networks (WSNs) that is based on a proposed connectivity-based RF localization strategy called the distributed Fermat-point location estimation algorithm (DFPLE). DFPLE applies trian...
Estimation of rice plant height distribution plays a significant role in keeping the feed rate of rice combine harvesters stable. This is an effective way to guarantee the working stability of the whole machine, as a consequence, improving threshing...
The aniline point (AP) is an important physical property of a petroleum fraction. The AP gives an indication of the aromatic hydrocarbon content in a hydrocarbon mixture and can also be an indicator of the ignition point of a diesel fraction. In this...
Determination of the relative pose of satellites is essential in space rendezvous operations and on-orbit servicing missions. The key problems are the adoption of suitable sensor on board of a chaser and efficient techniques for pose estimation. This...
A single VLP-16 LiDAR estimation method based on a single-frame 3D laser point cloud is proposed to address the problem of estimating negative obstacles’ geometrical features in structured environments. Firstly, a distance measurement method is devel...
Joint estimation of the human body is suitable for many fields such as human–computer interaction, autonomous driving, video analysis and virtual reality. Although many depth-based researches have been classified and generalized in previous review or...
In this paper, we investigate the CUSUM-type estimator of mean change-point models based on m-asymptotically almost negatively associated (m-AANA) sequences. The family of m-AANA sequences contains AANA, NA, m-NA, and independent sequences as special...
Graph Neural Networks (GNNs) are neural networks that learn the representation of nodes and associated edges that connect it to every other node while maintaining graph representation. Graph Convolutional Neural Networks (GCNs), as a representative m...
This study presents a methodology for the coarse alignment of light detection and ranging (LiDAR) point clouds, which involves estimating the position and orientation of each station using the pinhole camera model and a position/orientation estimatio...
Head pose estimation serves various applications, such as gaze estimation, fatigue-driven detection, and virtual reality. Nonetheless, achieving precise and efficient predictions remains challenging owing to the reliance on singular data sources. The...
To address the limitations of inadequate real-time performance and robustness encountered in estimating the pose of non-cooperative spacecraft during on-orbit missions, a novel method of feature point distribution selection learning is proposed. This...
Owing to imperfect scans, occlusions, low reflectance of the scanned surface, and packet loss, there may be several incomplete regions in the 3D point cloud dataset. These missing regions can degrade the performance of recognition, classification, se...
Pose estimation plays a crucial role in on-orbit servicing technologies. Currently, point cloud registration-based pose estimation methods for noncooperative spacecraft still face the issue of misalignment due to similar point cloud structural featur...
We propose a generative framework for 3D human pose estimation that is able to operate on both individual point sets and sequential depth data. We formulate human pose estimation as a point set registration problem, where we propose three new approac...
To facilitate the automation of crane operations for grabbing coil stacks in port storage areas, thereby streamlining the processes of warehousing, stacking, and transshipment for enhanced operational efficiency, this paper utilizes algorithms relate...
This paper proposes a new pose and focal length estimation method using two vanishing points and a known camera position. A vanishing point can determine the unit direction vector of the corresponding parallel lines in the camera frame, and as input,...
Vision-based pose estimation is an important application of machine vision. Currently, analytical and iterative methods are used to solve the object pose. The analytical solutions generally take less computation time. However, the analytical solution...
The task of tracking the pose of an object with a known geometry from point cloud measurements arises in robot perception. It calls for a solution that is both accurate and robust, and can be computed at a rate that aligns with the needs of a control...
In recent years, gaze estimation has received a lot of interest in areas including human–computer interface, virtual reality, and user engagement analysis. Despite significant advances in convolutional neural network (CNN) techniques, directly...
Moving objects in the environment have a higher priority and more challenges in growing domains like unmanned vehicles and intelligent robotics. Estimating the motion state of objects based on point clouds in outdoor scenarios is currently a challeng...
In industrial quality control, the precise identification of severe structural weld defects is paramount. Traditional 2D image-based detection methods are susceptible to illumination and texture interference, while high-precision 3D laser scanning so...
The mainstream image matching method for recovering the motion of the camera is based on local feature matching, which faces the challenges of rotation, illumination, and the presence of dynamic objects. In addition, local feature matching relies on...
This paper presents an estimation of the launching points of unmanned aerial vehicles (UAVs) equipped with boosters. When UAVs are detected and tracked by sensors such as radars, the fast identification of vehicle launching points is needed for air t...
The segmentation of jujube tree branches and the estimation of primary branch inclination angles (IAs) are crucial for achieving intelligent pruning. This study presents a primary branch IA estimation algorithm for jujube trees based on an improved P...
The precise knowledge of the point spread function is central for any imaging system characterization. In fluorescence microscopy, point spread function (PSF) determination has become a common and obligatory task for each new experimental device, mai...
The accurate attitude estimation of target ships plays a vital role in ensuring the safety of marine transportation, especially for tugs. A Light Detection and Ranging (LiDAR) system can generate 3D point clouds to describe the target ship’s ge...
Normal estimation is a crucial first step for numerous light detection and ranging (LiDAR) data-processing algorithms, from building reconstruction, road extraction, and ground-cover classification to scene rendering. For LiDAR point clouds in urban...
With the advancement of 5G-Advanced Non-Terrestrial Network (5G-A NTN) mobile communication technologies, direct satellite connectivity for mobile devices has been increasingly adopted. In the highly dynamic environment of low-Earth-orbit (LEO) satel...
The substantial data volume within dynamic point clouds representing three-dimensional moving entities necessitates advancements in compression techniques. Motion estimation (ME) is crucial for reducing point cloud temporal redundancy. Standard block...
Estimators derived from a divergence criterion such as
The aim of the perspective-three-point (P3P) problem is to estimate extrinsic parameters of a camera from three 2D–3D point correspondences, including the orientation and position information. All the P3P solvers have a multi-solution phenomenon that...
3D hand pose estimation has achieved remarkable progress in human computer interaction and computer vision; however, real-world hand point clouds often suffer from structural distortions such as partial occlusions, sensor noise, and environmental int...
We propose a point cloud-based framework for open-vocabulary object pose estimation, called Pov9D. Existing approaches are predominantly RGB-based and often rely on texture or appearance cues, making them susceptible to pose ambiguities when objects...
In the vehicle pose estimation task based on roadside Lidar in cooperative perception, the measurement distance, angle, and laser resolution directly affect the quality of the target point cloud. For incomplete and sparse point clouds, current method...
This paper proposes a 3D point-of-regard estimation method based on 3D eye model and a corresponding head-mounted gaze tracking device. Firstly, a head-mounted gaze tracking system is given. The gaze tracking device uses two pairs of stereo cameras t...
Point cloud densification is essential for understanding the 3D environment. It provides crucial structural and semantic information for downstream tasks such as 3D object detection and tracking. However, existing registration-based methods struggle...
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