Relevant bibliographies by topics / Joint coordinates estimation

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  1. Journal articles

Academic literature on the topic 'Joint coordinates estimation'

Author: Grafiati
Published: 15 February 2025

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Journal articles on the topic "Joint coordinates estimation"

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 joints of the hand are modeled by using graph convolution, and the feature information of the hand joints is enhanced by determining the relationship between the hand joints. Finally, the skeletal constraint loss function is used to impose constraints on the joints, and a natural and undistorted hand skeleton structure is generated. Training tests are conducted on the public gesture interaction dataset STB, and the experimental results show that the method in this paper can reduce errors in hand joint point detection and improve the estimation accuracy.
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2

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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3

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 the FMBPM, a digital single-lens reflex camera with a prime lens and a total station are the necessary hardware employed to capture images and measure the coordinates of feature points. A coordinate transformation means of converting model coordinates to physical coordinates was introduced. A program for calculating a joint orientation based on the coordinates of inflection points on the trace line of the joint was developed. A section of a rock slope was selected as a case to show the procedures and the practicability of the FMBPM. The textured 3D point cloud model of the rock slope was successfully built, and the rock structure of the rock slope was analyzed using the joint disk model generated based on the trace lines extracted from the point cloud model. The results show that: (1) the precision of the point coordinates of the textured 3D point cloud model could achieve 3.96 mm, taking the data of the total station as the reference; (2) the rock structure of the slope is good, according to the value of the rock quality designation; (3) the new method is applicable in engineering practices.
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4

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 multi-viewpoints. To expand to multi-viewpoints our proposed method first generates an 8-dimensional joint coordinate that connects 2-dimensional joint coordinates for 17 joints at 4-vieiwpoints acquired using the 2-dimensional human posture detector, CPN(Cascaded Pyramid Network). This paper then converts them into 17×32 data with patch embedding, and enters the data into a transformer model, finally. Consequently, the MLP(Multi-Layer Perceptron) block that outputs the 3D-human posture simultaneously updates the 3D human posture estimation for 4-viewpoints at every iteration. Compared to Zheng[5]'s method the number of model parameters of the proposed method was 48.9%, MPJPE(Mean Per Joint Position Error) was reduced by 20.6 mm (43.8%) and the average learning time per epoch was more than 20 times faster.
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5

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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6

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. Second, the REBA method was improved by using fuzzy logic theory to more effectively capture the slow transition features of continuous movement by humans without abruptly altering risk scores, as well as to increase the accuracy and consistency of posture risk evaluation. Third, joint torque and workloads were estimated using biomechanical calculations by integrating pressure insoles and 3D joint coordinate data. Experiments show that this method can effectively evaluate posture risks and workloads in manual material handling tasks, with a correlation coefficient of 0.817 ( p < 0.01 ) between fuzzy logic REBA and REBA and an error rate of 15% in estimating workloads of eight joints. This method can help reduce occupational health risks for workers and industries and improve work efficiency.
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7

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 are obtained preliminarily. Second, the posture coordinates are established according to the human motion parameters, and the curve running posture data is obtained and filtered to obtain more accurate data. Finally, the Bayesian network in machine learning is used to continuously track the posture, and a nonlinear equation is established to fuse the posture angle obtained by the sensor and the posture tracked by the Bayesian network, to realize the posture estimation of curve running motion. The results show that the proposed estimation method has a good motion posture estimation effect, and the hip joint estimation error, knee joint estimation error and ankle joint estimation error are all less than 5°, and the endpoint displacement estimation offset rate is less than 2%. It can realize accurate motion posture estimation of curve running motion, and has important application value in the field of track training.
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8

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, as well as the direction cosines of the vectors with the coordinate axes. The determination of the direction of displacement is shown for the transference deformation. And how to determine the axis, the distance to this axis and the angle of rotation is shown for rotation deformation. We show for joint deformation of the transfer and rotation how divide it into components and then determine the direction of displacement and the axis of rotation. The results can be used in assessing of absolute deformations buildings of monuments of cultural heritage.
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9

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 the coordinates of the elastic vibration tones, as well as an algorithm for the identification of their unobservable parameters are developed. The results of mathematical modeling of a variant of the mechanical system of a space structure are presented, which confirm the operability and efficiency of the developed algorithms for estimating coordinates and parameters.
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10

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 of received signal to the fusion center, each radar performs 2D MUSIC with its own received signal in the transformed coordinates. Accordingly, the distributed radars do not need to report all their measured signals to the data fusion center, but they forward their local cost function values of 2D MUSIC for the radar image region of interest. The data fusion center can then estimate the range and angle information of targets jointly from the aggregated cost function. By applying the proposed scheme to the experimentally measured data, its performance is verified in the real environment test.
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