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Journal articles on the topic 'Joint coordinates estimation'

Author: Grafiati

Published: 15 February 2025

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1

Rong, Dang, and Feng Gang. "Coordinate-Corrected and Graph-Convolution-Based Hand Pose Estimation Method." Sensors 24, no. 22 (2024): 7289. http://dx.doi.org/10.3390/s24227289.

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To address the problem of low accuracy in joint point estimation in hand pose estimation methods due to the self-similarity of fingers and easy self-obscuration of hand joints, a hand pose estimation method based on coordinate correction and graph convolution is proposed. First, the standard coordinate encoding is improved by generating an unbiased heat map, and the distribution-aware method is used for decoding coordinates to reduce the error in decoding the coordinate encoding of joints. Then, the complex dependency relationship between the joints and the relationship between pixels and join

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Goldenberg, A. A., J. A. Apkarian, and H. W. Smith. "A New Approach to Kinematic Control of Robot Manipulators." Journal of Dynamic Systems, Measurement, and Control 109, no. 2 (1987): 97–103. http://dx.doi.org/10.1115/1.3143843.

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A new approach for solving the inverse kinematics problem iteratively is presented. The solution is based on the recursive estimation of a kinematics operator which maps the task space coordinates into joint coordinates. The recursive estimation is based on least square approximation. For controlling the robot, the solution (Joint coordinates) must be compensated to achieve an arbitrarily small error (in least square sense) of the desired task space coordinates. The compensation is provided by closed loop feedback of task space coordinates using an optimal control approach.

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Liu, Tiexin, and Jianhui Deng. "Photogrammetry-Based 3D Textured Point Cloud Models Building and Rock Structure Estimation." Applied Sciences 13, no. 8 (2023): 4977. http://dx.doi.org/10.3390/app13084977.

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Trace lines on the outcrop of a rock mass are usually the primary data source for the estimation of rock structure. It is important to obtain the data of trace lines precisely. Photogrammetry is well suited to finish this task. However, this is mainly conducted by commercial software, and not every researcher has easy access to the method of digital photogrammetry. This study aims to provide researchers with a low-cost method of building a photogrammetry-based textured 3D point cloud model (FMBPM) and display the applicability of the method to estimating the rock structure of rock masses. In t

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Choi, Seoung Wook, Jin Young Lee, and Gye Young Kim. "Multi-View 3D Human Pose Estimation Based on Transformer." Korean Institute of Smart Media 12, no. 11 (2023): 48–56. http://dx.doi.org/10.30693/smj.2023.12.11.48.

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The technology of Three-dimensional human posture estimation is used in sports, motion recognition, and special effects of video media. Among various methods for this, multi-view 3D human pose estimation is essential for precise estimation even in complex real-world environments. But Existing models for multi-view 3D human posture estimation have the disadvantage of high order of time complexity as they use 3D feature maps. This paper proposes a method to extend an existing monocular viewpoint multi-frame model based on Transformer with lower time complexity to 3D human posture estimation for

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万, 云翀, Yunpeng Song, and Ligang Liu. "3D Human Pose Estimation Based on Volumetric Joint Coordinates." Journal of Computer-Aided Design & Computer Graphics 34, no. 09 (2022): 1411–19. http://dx.doi.org/10.3724/sp.j.1089.2022.19167.

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Wang, Ziao, Weixing Wang, Jingxi Chen, Xuzhuang Zhang, and Ziheng Miao. "Posture Risk Assessment and Workload Estimation for Material Handling by Computer Vision." International Journal of Intelligent Systems 2023 (October 25, 2023): 1–19. http://dx.doi.org/10.1155/2023/2085251.

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Workers in material handling tasks often suffer from work-related musculoskeletal disorders (WMSDs) caused by inaccurate work postures or the lifting of excessively heavy loads. Therefore, effective ergonomic assessment of workers is needed to improve worker productivity while reducing the risk of musculoskeletal disorders. This paper proposes a noninvasive method for evaluating posture risks and load analysis in manual material handling tasks. The study focuses on three main aspects: first, using 3D pose recognition technology to extract the 3D coordinates and joint angles of the human body.

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Wu, Xiaoming, Yu Cao, Yu Wang, Bing Li, Haitao Yang, and S. P. Raja. "Posture Estimation of Curve Running Motion Using Nano-Biosensor and Machine Learning." International Journal of Interactive Multimedia and Artificial Intelligence In Press, In Press (2024): 1–9. http://dx.doi.org/10.9781/ijimai.2024.07.001.

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Curve running is a common form of training and competition. Conducting research on posture estimation during curve running can provide more accurate training and competition data for athletes. However, due to the unique nature of curve running, traditional posture estimation methods neglect the temporal changes in athlete posture, resulting in a decrease in estimation accuracy. Therefore, a posture estimation method for curve running motion using nano-biosensor and machine learning is proposed. First, the motion parameters of humans are collected by nano-biosensor, and the posture coordinates

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Tsareva, Olga, Ivan Dmitriev, and Yuriy Kornilov. "Estimation of absolute deformations by changes in distances between the reference points and deformation marks." MATEC Web of Conferences 245 (2018): 04013. http://dx.doi.org/10.1051/matecconf/201824504013.

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The article considers the definition of absolute types of deformations, such as transfer and rotation of a building, using linear spatial intersection. In particular, knowing the distances between strong points and deformation marks, the coordinates of the marks located on the building in the initial and current observation cycles are obtained. Knowing the coordinates of the marks, calculate the displacement vectors of the marks for a certain period of time. The definition of absolute deformations is based on the estimation of the projections of the displacement vectors on the coordinate axes,

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Rutkovskiy, V. Yu, V. M. Glumov, and A. S. Ermilov. "Angular Motion Control of a Large Space Structure with Elastic Elements." Avtomatika i telemehanika, no. 8 (December 15, 2023): 122–37. http://dx.doi.org/10.31857/s0005231023080081.

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The task of angular orientation and stabilization of a space structure during its assembly in orbit is solved. The structure includes elastic elements that are installed during the assembly process. The elastic elements of the structure have no sensors to obtain information about their deformation parameters. Control algorithms are proposed to ensure the stability of the angular motion of the structure. A nonlinear extended Kalman filter is used to obtain the necessary information. A joint estimation algorithm for the coordinates of the angular motion of the considered mechanical system and th

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Seo, Jiho, Jonghyeok Lee, Jaehyun Park, Hyungju Kim, and Sungjin You. "Distributed Two-Dimensional MUSIC for Joint Range and Angle Estimation with Distributed FMCW MIMO Radars." Sensors 21, no. 22 (2021): 7618. http://dx.doi.org/10.3390/s21227618.

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To estimate range and angle information of multiple targets, FMCW MIMO radars have been exploited with 2D MUSIC algorithms. To improve estimation accuracy, received signals from multiple FMCW MIMO radars are collected at the data fusion center and processed coherently, which increases data communication overhead and implementation complexity. To resolve them, we propose the distributed 2D MUSIC algorithm with coordinate transformation, in which 2D MUSIC algorithm is operated with respect to the reference radar’s coordinate at each radar in a distributed way. Rather than forwarding the raw data

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Li, Moran, Yuan Gao, and Nong Sang. "Exploiting Learnable Joint Groups for Hand Pose Estimation." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 3 (2021): 1921–29. http://dx.doi.org/10.1609/aaai.v35i3.16287.

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In this paper, we propose to estimate 3D hand pose by recovering the 3D coordinates of joints in a group-wise manner, where less-related joints are automatically categorized into different groups and exhibit different features. This is different from the previous methods where all the joints are considered holistically and share the same feature. The benefits of our method are illustrated by the principle of multi-task learning (MTL), i.e., by separating less-related joints into different groups (as different tasks), our method learns different features for each of them, therefore efficiently

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Nechaev, Yury Borisovich, Ilia Vladimirovich Peshkov, Nataliya Alexandrovna Fortunova, Irina Nikolaevna Zaitseva, and Eugene Alexandrovich Arnautov. "Improving the shapes of planar antenna arrays to improve accuracy of radar with super-resolution." Vestnik of Astrakhan State Technical University. Series: Management, computer science and informatics 2022, no. 3 (2022): 38–50. http://dx.doi.org/10.24143/2072-9502-2022-3-38-50.

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A promising way to increase the bandwidth and noise immunity of modern wireless information transmission systems is the use of antenna arrays equipped with a digital signal processing unit, which include MIMO systems (Multiple Input Multiple Output), as well as adaptive (smart) antennas. The main advantage of this approach is the antenna’s spacing, which makes it possible to assess the angular coordinates of radio signals with further developing  a radiation pattern. Gaps in studying the influence of the lattice geometry together with various kinds of antenna elements are known to be one

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Cai, Qingyuan, Xuecai Hu, Saihui Hou, Li Yao, and Yongzhen Huang. "Disentangled Diffusion-Based 3D Human Pose Estimation with Hierarchical Spatial and Temporal Denoiser." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 2 (2024): 882–90. http://dx.doi.org/10.1609/aaai.v38i2.27847.

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Recently, diffusion-based methods for monocular 3D human pose estimation have achieved state-of-the-art (SOTA) performance by directly regressing the 3D joint coordinates from the 2D pose sequence. Although some methods decompose the task into bone length and bone direction prediction based on the human anatomical skeleton to explicitly incorporate more human body prior constraints, the performance of these methods is significantly lower than that of the SOTA diffusion-based methods. This can be attributed to the tree structure of the human skeleton. Direct application of the disentangled meth

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Ferretti, G., C. Maffezzoni, G. Magnani, and P. Rocco. "Joint Stiffness Estimation Based on Force Sensor Measurements in Industrial Manipulators." Journal of Dynamic Systems, Measurement, and Control 116, no. 1 (1994): 163–67. http://dx.doi.org/10.1115/1.2900673.

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The problem of estimating the stiffness constants of the joints in industrial manipulators is addressed in this paper. It is shown that the model of the robot constrained by a rigid environment yields a simple relationship between variations of the motor coordinates and the forces arising at the contact with the environment. By exploiting the measurements of the motor positions sensors and of a force sensor located at the end effector a method is proposed to simply compute good estimates of the stiffness constants. Experiments have been made on the industrial robot SMART and the results are gi

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Wenjing Ma, Wenjing Ma, Jianguang Zhao Wenjing Ma, and Guangquan Zhu Jianguang Zhao. "Estimation on Human Motion Posture using Improved Deep Reinforcement Learning." 電腦學刊 34, no. 4 (2023): 097–110. http://dx.doi.org/10.53106/199115992023083404008.

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<p>Estimating human motion posture can provide important data for intelligent monitoring systems, human-computer interaction, motion capture, and other fields. However, the traditional human motion posture estimation algorithm is difficult to achieve the goal of fast estimation of human motion posture. To address the problems of traditional algorithms, in the paper, we propose an estimation algorithm for human motion posture using improved deep reinforcement learning. First, the double deep Q network is constructed to improve the deep reinforcement learning algorithm. The improved deep r

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Huang, Weiting, Pengfei Ren, Jingyu Wang, Qi Qi, and Haifeng Sun. "AWR: Adaptive Weighting Regression for 3D Hand Pose Estimation." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 07 (2020): 11061–68. http://dx.doi.org/10.1609/aaai.v34i07.6761.

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In this paper, we propose an adaptive weighting regression (AWR) method to leverage the advantages of both detection-based and regression-based method. Hand joint coordinates are estimated as discrete integration of all pixels in dense representation, guided by adaptive weight maps. This learnable aggregation process introduces both dense and joint supervision that allows end-to-end training and brings adaptability to weight maps, making network more accurate and robust. Comprehensive exploration experiments are conducted to validate the effectiveness and generality of AWR under various experi

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17

Park, Byung-Seo, Woosuk Kim, Jin-Kyum Kim, Eui Seok Hwang, Dong-Wook Kim, and Young-Ho Seo. "3D Static Point Cloud Registration by Estimating Temporal Human Pose at Multiview." Sensors 22, no. 3 (2022): 1097. http://dx.doi.org/10.3390/s22031097.

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This paper proposes a new technique for performing 3D static-point cloud registration after calibrating a multi-view RGB-D camera using a 3D (dimensional) joint set. Consistent feature points are required to calibrate a multi-view camera, and accurate feature points are necessary to obtain high-accuracy calibration results. In general, a special tool, such as a chessboard, is used to calibrate a multi-view camera. However, this paper uses joints on a human skeleton as feature points for calibrating a multi-view camera to perform calibration efficiently without special tools. We propose an RGB-

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Izadbakhsh, Alireza, and Saeed Khorashadizadeh. "Robust task-space control of robot manipulators using differential equations for uncertainty estimation." Robotica 35, no. 9 (2016): 1923–38. http://dx.doi.org/10.1017/s0263574716000588.

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SUMMARYMost control algorithms for rigid-link electrically driven robots are given in joint coordinates. However, since the task to be accomplished is expressed in Cartesian coordinates, inverse kinematics has to be computed in order to implement the control law. Alternatively, one can develop the necessary theory directly in workspace coordinates. This has the disadvantage of a more complex robot model. In this paper, a robust control scheme is given to achieve exact Cartesian tracking without the knowledge of the manipulator kinematics and dynamics, actuator dynamics and nor computing invers

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Qin, Yuemei, Yang Han, Shuying Li, and Jun Li. "An Iteratively Extended Target Tracking by Using Decorrelated Unbiased Conversion of Nonlinear Measurements." Sensors 24, no. 5 (2024): 1362. http://dx.doi.org/10.3390/s24051362.

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Extended target tracking (ETT) based on random matrices typically assumes that the measurement model is linear. However, nonlinear measurements (such as range and azimuth) depending on locations of a series of unknown scattering centers always exist in many practical tracking applications. To address this issue, this paper proposes an iteratively extended target tracking based on random matrices by using decorrelated unbiased conversion of nonlinear measurements (ETT-IDUCM). First, we utilize a decorrelated unbiased converted measurement (DUCM) method to convert nonlinear measurements dependin

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20

Chen, Jian, Hui Zhao, Xiaoying Sun, and Guohong Liu. "Joint 2D Direction-of-Arrival and Range Estimation for Nonstationary Sources." International Journal of Antennas and Propagation 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/849039.

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Passive localization of nonstationary sources in the spherical coordinates (azimuth, elevation, and range) is considered, and a parallel factor analysis based method is addressed for the near-field parameter estimation problem. In this scheme, a parallel factor analysis model is firstly constructed by computing five time-frequency distribution matrices of the properly chosen observation data. In addition, the uniqueness of the constructed model is proved, and both the two-dimensional (2D) direction-of-arrival (DOA) and range can be jointly obtained via trilinear alternating least squares regre

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Xue, Feng, Fuli Bian, and Shujie Li. "Attention fusion network for estimation of 3D joint coordinates and rotation of human pose." Journal of Image and Graphics 29, no. 10 (2024): 3116–29. http://dx.doi.org/10.11834/jig.230502.

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Huang, Xin, Yuanping Zhu, and Shuqin Wang. "An Efficient Dynamic Regulated Fuzzy Neural Network for Human Motion Retrieval and Analysis." Symmetry 13, no. 8 (2021): 1317. http://dx.doi.org/10.3390/sym13081317.

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Human motion retrieval and analysis is a useful means of activity recognition to 3D human bodies. An efficient method is proposed to estimate human motion by using symmetric joint points and limb features of various limb parts based on regression task. We primarily obtain the 3D coordinates of symmetric joint points based on the located waist and hip points. By introducing three critical feature points on torso and symmetric joint points’ matching on motion video sequences, the 3D coordinates of symmetric joint points and its asymmetric limb features will not be affected by shading and interfe

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Pagnon, David, Mathieu Domalain, and Lionel Reveret. "Pose2Sim: An End-to-End Workflow for 3D Markerless Sports Kinematics—Part 2: Accuracy." Sensors 22, no. 7 (2022): 2712. http://dx.doi.org/10.3390/s22072712.

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Two-dimensional deep-learning pose estimation algorithms can suffer from biases in joint pose localizations, which are reflected in triangulated coordinates, and then in 3D joint angle estimation. Pose2Sim, our robust markerless kinematics workflow, comes with a physically consistent OpenSim skeletal model, meant to mitigate these errors. Its accuracy was concurrently validated against a reference marker-based method. Lower-limb joint angles were estimated over three tasks (walking, running, and cycling) performed multiple times by one participant. When averaged over all joint angles, the coef

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Yadav, Santosh Kumar, Kamlesh Tiwari, Hari Mohan Pandey, and Shaik Ali Akbar. "Skeleton-based human activity recognition using ConvLSTM and guided feature learning." Soft Computing 26, no. 2 (2021): 877–90. http://dx.doi.org/10.1007/s00500-021-06238-7.

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AbstractHuman activity recognition aims to determine actions performed by a human in an image or video. Examples of human activity include standing, running, sitting, sleeping, etc. These activities may involve intricate motion patterns and undesired events such as falling. This paper proposes a novel deep convolutional long short-term memory (ConvLSTM) network for skeletal-based activity recognition and fall detection. The proposed ConvLSTM network is a sequential fusion of convolutional neural networks (CNNs), long short-term memory (LSTM) networks, and fully connected layers. The acquisitio

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Dumas, R., E. Nicol, and L. Chèze. "Influence of the 3D Inverse Dynamic Method on the Joint Forces and Moments During Gait." Journal of Biomechanical Engineering 129, no. 5 (2007): 786–90. http://dx.doi.org/10.1115/1.2768114.

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The joint forces and moments are commonly used in gait analysis. They can be computed by four different 3D inverse dynamic methods proposed in the literature, either based on vectors and Euler angles, wrenches and quaternions, homogeneous matrices, or generalized coordinates and forces. In order to analyze the influence of the inverse dynamic method, the joint forces and moments were computed during gait on nine healthy subjects. A ratio was computed between the relative dispersions (due to the method) and the absolute amplitudes of the gait curves. The influence of the inverse dynamic method

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Li, Shaobo, Xingxing Zhang, Jing Yang, et al. "Real-time motion tracking of cognitive Baxter robot based on differential inverse kinematics." International Journal of Advanced Robotic Systems 18, no. 3 (2021): 172988142110240. http://dx.doi.org/10.1177/17298814211024052.

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The tracking motion of the robot is realized based on a specific robot or relying on an expensive movement acquisition system. It has the problems of complex control procedures, lack of real-time performance, and difficulty in achieving secondary development. We propose a robot real-time tracking control method based on the control principle of differential inverse kinematics, which fuses the position and joint angle information of the robot’s actuators to realize the real-time estimation of the user’s movement during the tracking process. The motion coordinates of each joint of the robot are

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Sahota, Herman, and Ratnesh Kumar. "Sensor Localization Using Time of Arrival Measurements in a Multi-Media and Multi-Path Application of In-Situ Wireless Soil Sensing." Inventions 6, no. 1 (2021): 16. http://dx.doi.org/10.3390/inventions6010016.

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The problem of localization of nodes of a wireless sensor network placed in different physical media (anchor nodes above ground and sensor nodes underground) is addressed in this article. We use time of arrival of signals transmitted between neighboring sensor nodes and between satellite nodes and sensor nodes as the ranging measurement. The localization problem is formulated as a parameter estimation of the joint distribution of the time of arrival values. The probability distribution of the time of arrival of a signal is derived based on rigorous statistical analysis and its parameters are e

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Nenashev, Vadim, and Alexander Shepeta. "Accuracy characteristics of object location in a two-position system of small onboard radars." Information and Control Systems, no. 2 (April 20, 2020): 31–36. http://dx.doi.org/10.31799/1684-8853-2020-2-31-36.

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Introduction: The search for physical objects in a given area is often performed in automatic mode using small unmanned aerial vehicles equipped with radars. Airborne radar antennas, due to size restrictions, have a small aperture and, accordingly, a wide directional pattern, decreasing the accuracy of determining the angular coordinates of the objects. The increase in the angular coordinate estimation accuracy leads to the increase in the informativeness of such automatic search systems and, consequently, to the increase in the efficiency of their practical use. Purpose: Developing a techniqu

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yuchi, atsushi, takahiko sato, and akinori nagano. "Estimation Of Joint Torque During Countermovement Jump From Position Coordinates Using Deep Residual Recurrent Network." Medicine & Science in Sports & Exercise 52, no. 7S (2020): 272. http://dx.doi.org/10.1249/01.mss.0000676520.42951.58.

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Martinez, Lucas, Matthieu Lalevée, Thomas Poirier, et al. "Influence of Skin Marker Positioning and Their Combinations on Hip Joint Center Estimation Using the Functional Method." Bioengineering 11, no. 3 (2024): 297. http://dx.doi.org/10.3390/bioengineering11030297.

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Accurate estimation of hip joint center (HJC) position is crucial during gait analysis. HJC is obtained with predictive or functional methods. But in the functional method, there is no consensus on where to place the skin markers and which combination to use. The objective of this study was to analyze how different combinations of skin markers affect the estimation of HJC position relative to predictive methods. Forty-one healthy volunteers were included in this study; thirteen markers were placed on the pelvis and hip of each subject’s lower limbs. Various marker combinations were used to det

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Takigami, Shunsaku, Atsuyuki Inui, Yutaka Mifune, et al. "Estimation of Shoulder Joint Rotation Angle Using Tablet Device and Pose Estimation Artificial Intelligence Model." Sensors 24, no. 9 (2024): 2912. http://dx.doi.org/10.3390/s24092912.

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Traditionally, angle measurements have been performed using a goniometer, but the complex motion of shoulder movement has made these measurements intricate. The angle of rotation of the shoulder is particularly difficult to measure from an upright position because of the complicated base and moving axes. In this study, we attempted to estimate the shoulder joint internal/external rotation angle using the combination of pose estimation artificial intelligence (AI) and a machine learning model. Videos of the right shoulder of 10 healthy volunteers (10 males, mean age 37.7 years, mean height 168.

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Wierzcholski, Krzysztof, and Ryszard Maciołek. "A NEW CONTRIBUTION IN STOCHASTIC HYDRODYNAMIC LUBRICATION FOR ARBITRARY BIO-SURFACES." Tribologia 291, no. 3 (2020): 63–76. http://dx.doi.org/10.5604/01.3001.0014.4766.

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This paper shows a recent progress described in curvilinear, orthogonal coordinates of the method of estimation of stochastic bio-hydrodynamic lubrication parameters. Here are discussed real arbitrary movable, non-rotational living biological surfaces coated with phospholipid bi-layers and lubricated with biological liquids. Non-rotational, curvilinear cooperating biological surfaces take the place in various biological nods for example in sacra bone, femoral bone, knee cap, calf bone and hip joint, elbow joint, knee joint, jump joint. Moreover are assumed biological non-rotational friction no

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Shiao, Yaojung, Guan-Yu Chen, and Thang Hoang. "Three-Dimensional Human Posture Recognition by Extremity Angle Estimation with Minimal IMU Sensor." Sensors 24, no. 13 (2024): 4306. http://dx.doi.org/10.3390/s24134306.

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Recently, posture recognition technology has advanced rapidly. Herein, we present a novel posture angle calculation system utilizing a single inertial measurement unit and a spatial geometric equation to accurately identify the three-dimensional (3D) motion angles and postures of both the upper and lower limbs of the human body. This wearable system facilitates continuous monitoring of body movements without the spatial limitations or occlusion issues associated with camera-based methods. This posture-recognition system has many benefits. Providing precise posture change information helps user

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Woo, Yeong Ju, Ji-Yong Joo, Young-Kwan Kim, and He Yong Jeong. "Analysis of Pitching Motions by Human Pose Estimation Based on RGB Images." Korean Institute of Smart Media 13, no. 4 (2024): 16–22. http://dx.doi.org/10.30693/smj.2024.13.4.16.

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Pitching is a major part of baseball, so much so that it can be said to be the beginning of baseball. Analysis of accurate pitching motions is very important in terms of performance improvement and injury prevention. When analyzing the correct pitching motion, the currently used motion capture method has several critical environmental drawbacks. In this paper, we propose analysis of pitching motion using the RGB-based Human Pose Estimation (HPE) model to replace motion capture, which has these shortcomings, and use motion capture data and HPE data to verify its reliability. The similarity of t

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Zhang, Siqi, Jie Jin, Chaofang Wang, Wenlong Dong, and Bin Fan. "Quality Evaluation Algorithm for Chest Compressions Based on OpenPose Model." Applied Sciences 12, no. 10 (2022): 4847. http://dx.doi.org/10.3390/app12104847.

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Aiming at the problems of the low evaluation efficiency of the existing traditional cardiopulmonary resuscitation (CPR) training mode and the considerable development of machine vision technology, a quality evaluation algorithm for chest compressions (CCs) based on the OpenPose human pose estimation (HPE) model is proposed. Firstly, five evaluation criteria are proposed based on major international CPR guidelines along with our experimental study on elbow straightness. Then, the OpenPose network is applied to obtain the coordinates of the key points of the human skeleton. The algorithm subsequ

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Wang, Dianjun, zilong wang, Ya Chen, Zhiguo Cui, Yadong Zhu, and Chao Wu. "Kinematics analysis and calibration of a 6-degree of freedom light load collaborative robot." Cobot 1 (September 15, 2022): 18. http://dx.doi.org/10.12688/cobot.17568.1.

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Background: In the process of carrying small forgings and other materials, the trajectory error of the 6-degree of freedom light-load collaborative robot will lead to the deviation of forgings placement position. The kinematics analysis and calibration of 6-degree of freedom light load collaborative robot are performed to solve the problem of trajectory error. Methods: The quaternion and cubic spline interpolation methods are adopted to plan the trajectory of the 6-degree of freedom light load collaborative robot. Based on the kinematic error model, the least squares estimation method is adopt

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Shin, Jungpil, Akitaka Matsuoka, Md Al Mehedi Hasan, and Azmain Yakin Srizon. "American Sign Language Alphabet Recognition by Extracting Feature from Hand Pose Estimation." Sensors 21, no. 17 (2021): 5856. http://dx.doi.org/10.3390/s21175856.

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Sign language is designed to assist the deaf and hard of hearing community to convey messages and connect with society. Sign language recognition has been an important domain of research for a long time. Previously, sensor-based approaches have obtained higher accuracy than vision-based approaches. Due to the cost-effectiveness of vision-based approaches, researchers have been conducted here also despite the accuracy drop. The purpose of this research is to recognize American sign characters using hand images obtained from a web camera. In this work, the media-pipe hands algorithm was used for

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Kitajima, Eiji, Takashi Sato, Koji Kurata, and Ryota Miyata. "Automatic feature selection for performing Unit 2 of vault in wheel gymnastics." PLOS ONE 18, no. 6 (2023): e0287095. http://dx.doi.org/10.1371/journal.pone.0287095.

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We propose a framework to analyze the relationship between the movement features of a wheel gymnast around the mounting phase of Unit 2 of the vault event and execution (E-score) deductions from a machine-learning perspective. We first developed an automation system from a video of a wheel gymnast performing a tuck-front somersault to extract the four frames highlighting its Unit 2 performance of the vault event, such as take-off, pike-mount, the starting point of time on the wheel, and final position before the thrust. We implemented this automation using recurrent all-pairs field transforms

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Bao, Wenxia, Zhongyu Ma, Dong Liang, Xianjun Yang, and Tao Niu. "Pose ResNet: 3D Human Pose Estimation Based on Self-Supervision." Sensors 23, no. 6 (2023): 3057. http://dx.doi.org/10.3390/s23063057.

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The accurate estimation of a 3D human pose is of great importance in many fields, such as human–computer interaction, motion recognition and automatic driving. In view of the difficulty of obtaining 3D ground truth labels for a dataset of 3D pose estimation techniques, we take 2D images as the research object in this paper, and propose a self-supervised 3D pose estimation model called Pose ResNet. ResNet50 is used as the basic network for extract features. First, a convolutional block attention module (CBAM) was introduced to refine selection of significant pixels. Then, a waterfall atrous spa

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Zhou, Yuting, and Hongjie Wan. "Joint Measurement of Multi-channel Sound Event Detection and Localization Using Deep Neural Network." Journal of Physics: Conference Series 2216, no. 1 (2022): 012101. http://dx.doi.org/10.1088/1742-6596/2216/1/012101.

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Abstract For joint sound event localization and detection (SELD), a multi-channel sound event method based on deep learning is proposed. This paper uses CRNN model training with datasets of maximum two overlapping sound events. The difficulty of the polyphonic SELD is the combination of SED and DOA estimation in the same network. Using multi-channel audio can better identify these overlapping sound events. The input of the proposed model is a series of continuous spectrograms, which are then output to two branches respectively. As the first branch, SED performs multi-label classification in ea

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Xu, Chenxin, Siheng Chen, Maosen Li, and Ya Zhang. "Invariant Teacher and Equivariant Student for Unsupervised 3D Human Pose Estimation." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 4 (2021): 3013–21. http://dx.doi.org/10.1609/aaai.v35i4.16409.

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We propose a novel method based on teacher-student learning framework for 3D human pose estimation without any 3D annotation or side information. To solve this unsupervised-learning problem, the teacher network adopts pose-dictionary-based modeling for regularization to estimate a physically plausible 3D pose. To handle the decomposition ambiguity in the teacher network, we propose a cycle-consistent architecture promoting a 3D rotation-invariant property to train the teacher network. To further improve the estimation accuracy, the student network adopts a novel graph convolution network for f

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Yuan, Chunmiao, Pengju Zhang, Qingyong Yang, and Jianming Wang. "Fall Detection and Direction Judgment Based on Posture Estimation." Discrete Dynamics in Nature and Society 2022 (June 15, 2022): 1–12. http://dx.doi.org/10.1155/2022/8372291.

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For the problem of elderly people falling easily, it is very necessary to correctly detect the occurrence of falls and provide early warning, which can greatly reduce the injury caused by falls. Most of the existing fall detection algorithms require the monitored persons to carry wearable devices, which will bring inconvenience to their lives and few algorithms pay attention to the direction of the fall. Therefore, we propose a video-based fall detection and direction judgment method based on human posture estimation for the first time. We predict the joint point coordinates of each human body

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Kondo, Tamon, Sakura Narumi, Zixun He, Duk Shin, and Yousun Kang. "A Performance Comparison of Japanese Sign Language Recognition with ViT and CNN Using Angular Features." Applied Sciences 14, no. 8 (2024): 3228. http://dx.doi.org/10.3390/app14083228.

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In recent years, developments in deep learning technology have driven significant advancements in research aimed at facilitating communication with individuals who have hearing impairments. The focus has been on enhancing automatic recognition and translation systems for sign language. This study proposes a novel approach using a vision transformer (ViT) for recognizing Japanese Sign Language. Our method employs a pose estimation library, MediaPipe, to extract the positional coordinates of each finger joint within video frames and generate one-dimensional angular feature data from these coordi

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Galkin, P. S., and V. N. Lagutkin. "METHOD OF COMPENSATION OF IONOSPHERE ERRORS OF SPACE OBJECTS COORDINATES DEFINITION BY MEANS OF TWO POSITION RADAR OBSERVATION." Issues of radio electronics, no. 3 (March 20, 2018): 45–49. http://dx.doi.org/10.21778/2218-5453-2018-3-45-49.

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The algorithm of estimation and compensation of ionosphere influence on the measurement of parameters of the motion of space objects in two-position radar system with account of radio physical effects depending on elevation angles and the operating frequency is developed. It is assumed that the observed space object is traсked object, the orbital parameters which are well known, including the dependence of the velocity of the point on the orbit, and the uncertainty of the current coordinates of the object is caused mainly by forecast error of its position of in orbit (longitudinal error). To e

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Lekova, A., A. Krastev, and I. Chavdarov. "Wireless Kinect-NAO Framework Based on Takagi-Sugeno Fuzzy Inference System." Information Technologies and Control 15, no. 2 (2017): 14–24. http://dx.doi.org/10.1515/itc-2017-0023.

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Abstract In the context of learning new skills by imitation for children with special educational needs, we propose Wireless Kinect-NAO Framework (WKNF) for robot teleoperation in real time based on Takagi-Sugeno (T-S) Fuzzy Inference System. The new solutions here are related to complex whole-body motion retargeting, standing body stabilization, view invariance and smoothness of robot motions. The raw depth Kinect data are fuzzified and processed by median filter. The joint angles estimation for motion mapping of Human to NAO movements is based on fuzzy logic and featured angles rather than d

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Zhao, Jingjing, Yongxiang Liu, Kai Huo, Jiaxi Ye, and Bo Xiao. "Three-Dimensional High-Resolution MIMO Radar Imaging via OFDM Modulation and Unitary ESPRIT." Mathematical Problems in Engineering 2020 (June 27, 2020): 1–16. http://dx.doi.org/10.1155/2020/2308389.

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Imaging and recognition of targets with complex maneuvers bring a new challenge to conventional radar applications. In this paper, the three-dimensional (3D) high-resolution image is attained in real-time by a Multiple-Input-Multiple-Output (MIMO) radar system with single Orthogonal-Frequency-Division-Multiplexing (OFDM) pulse. First, to build the orthogonal transmit waveform set for MIMO transmission, we utilize complex orthogonal designs (CODs) for OFDM subcarrier modulation. Based on the OFDM modulation, a preprocessing method is developed for transmit waveform separation without convention

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Zhang, Shaobo, Qinxiang Xia, Mingxing Chen, and Sizhu Cheng. "Multi-Objective Optimal Trajectory Planning for Robotic Arms Using Deep Reinforcement Learning." Sensors 23, no. 13 (2023): 5974. http://dx.doi.org/10.3390/s23135974.

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This study investigated the trajectory-planning problem of a six-axis robotic arm based on deep reinforcement learning. Taking into account several characteristics of robot motion, a multi-objective optimization approach is proposed, which was based on the motivations of deep reinforcement learning and optimal planning. The optimal trajectory was considered with respect to multiple objectives, aiming to minimize factors such as accuracy, energy consumption, and smoothness. The multiple objectives were integrated into the reinforcement learning environment to achieve the desired trajectory. Bas

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Lafayette, Thiago Buarque de Gusmão, Victor Hugo de Lima Kunst, Pedro Vanderlei de Sousa Melo, et al. "Validation of Angle Estimation Based on Body Tracking Data from RGB-D and RGB Cameras for Biomechanical Assessment." Sensors 23, no. 1 (2022): 3. http://dx.doi.org/10.3390/s23010003.

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Motion analysis is an area with several applications for health, sports, and entertainment. The high cost of state-of-the-art equipment in the health field makes it unfeasible to apply this technique in the clinics’ routines. In this vein, RGB-D and RGB equipment, which have joint tracking tools, are tested with portable and low-cost solutions to enable computational motion analysis. The recent release of Google MediaPipe, a joint inference tracking technique that uses conventional RGB cameras, can be considered a milestone due to its ability to estimate depth coordinates in planar images. In

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Kudriashov, Volodymyr V., Artem Y. Garbar, Konstantin A. Lukin, Lukasz Maslikowski, Piotr Samczynski, and Krzysztof S. Kulpa. "Fusion of Images Generated by Radiometric and Active Noise SAR." Cybernetics and Information Technologies 15, no. 7 (2015): 58–66. http://dx.doi.org/10.1515/cait-2015-0089.

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Abstract The work is devoted to fusion of radar and radiometer images. Noise waveform SAR generates radar images of reflective objects of its field of view. A bistatic radiometer with synthetic aperture estimates the thermal radio emissions of the objects along their angular coordinates and even range. The estimated brightness temperatures of rough and smooth surfaces are different, as well as the radar responses from them. Identification of the parameters of objects surfaces may be done using results of joint processing of images generated by both sensors. The optimum and quasi-optimum criter

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Iversen, Einar, and Martin Tygel. "Image-ray tracing for joint 3D seismic velocity estimation and time-to-depth conversion." GEOPHYSICS 73, no. 3 (2008): S99—S114. http://dx.doi.org/10.1190/1.2907736.

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Seismic time migration is known for its ability to generate well-focused and interpretable images, based on a velocity field specified in the time domain. A fundamental requirement of this time-migration velocity field is that lateral variations are small. In the case of 3D time migration for symmetric elementary waves (e.g., primary PP reflections/diffractions, for which the incident and departing elementary waves at the reflection/diffraction point are pressure [P] waves), the time-migration velocity is a function depending on four variables: three coordinates specifying a trace point locati

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