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Artykuły w czasopismach na temat „Motion Estimation”

Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 25 lipca 2025

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1

Qin, Yongming, Makoto Kumon, and Tomonari Furukawa. "Estimation of a Human-Maneuvered Target Incorporating Human Intention." Sensors 21, no. 16 (2021): 5316. http://dx.doi.org/10.3390/s21165316.

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This paper presents a new approach for estimating the motion state of a target that is maneuvered by an unknown human from observations. To improve the estimation accuracy, the proposed approach associates the recurring motion behaviors with human intentions, and models the association as an intention-pattern model. The human intentions relate to labels of continuous states; the motion patterns characterize the change of continuous states. In the preprocessing, an Interacting Multiple Model (IMM) estimation technique is used to infer the intentions and extract motions, which eventually constru

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Choi, Hee-Eun, and Jung-Il Jun. "Development of an Estimation Formula to Evaluate Mission Motion Suitability of Military Jackets." Applied Sciences 11, no. 19 (2021): 9129. http://dx.doi.org/10.3390/app11199129.

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We developed an estimation formula for mission motion suitability evaluation based on the general motion protocol to evaluate the motion suitability of a tracked vehicle crew jacket. Motion suitability evaluation was conducted for the 9 general motions and 12 mission motions among 27 tracked vehicle crew members who wore a tracked vehicle crew jacket. We conducted correlation and factor analyses on motions to extract the main mission motions, and a multiple regression analysis was performed on major mission motions using general motions as independent variables. As a result, two mission behavi

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3

Wan, Min, John J. Healy, and John T. Sheridan. "Fast 2D Subpixel Displacement Estimation." Photonics 11, no. 7 (2024): 625. http://dx.doi.org/10.3390/photonics11070625.

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Fast and simple methods for motion estimation with subpixel accuracy are of interest in a variety of applications. In this paper, we extend a recently proposed method for quantifying 1D displacements with subpixel accuracy, referred to as the subtraction method (SM) to 2D motion. Simulation and experimental results are presented. The results indicate that any general motion in 2D involving combinations of in-plane motions in x and y can be determined using SM after a 1D calibration. The errors between the actual motion and estimated are examined.

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4

Wang, Kaihong, Kumar Akash, and Teruhisa Misu. "Learning Temporally and Semantically Consistent Unpaired Video-to-Video Translation through Pseudo-Supervision from Synthetic Optical Flow." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 3 (2022): 2477–86. http://dx.doi.org/10.1609/aaai.v36i3.20148.

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Unpaired video-to-video translation aims to translate videos between a source and a target domain without the need of paired training data, making it more feasible for real applications. Unfortunately, the translated videos generally suffer from temporal and semantic inconsistency. To address this, many existing works adopt spatiotemporal consistency constraints incorporating temporal information based on motion estimation. However, the inaccuracies in the estimation of motion deteriorate the quality of the guidance towards spatiotemporal consistency, which leads to unstable translation. In th

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5

Li, Jiaman, C. Karen Liu, and Jiajun Wu. "Ego-Body Pose Estimation via Ego-Head Pose Estimation." AI Matters 9, no. 2 (2023): 20–23. http://dx.doi.org/10.1145/3609468.3609473.

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Estimating 3D human motion from an ego-centric video, which records the environment viewed from the first-person perspective with a front-facing monocular camera, is critical to applications in VR/AR. However, naively learning a mapping between egocentric videos and full-body human motions is challenging for two reasons. First, modeling this complex relationship is difficult; unlike reconstruction motion from third-person videos, the human body is often out of view of an egocentric video. Second, learning this mapping requires a large-scale, diverse dataset containing paired egocentric videos

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6

Zhou, Xuyang, Wei Jia, Ruofei He, and Wei Sun. "High-Precision Localization Tracking and Motion State Estimation of Ground-Based Moving Target Utilizing Unmanned Aerial Vehicle High-Altitude Reconnaissance." Remote Sensing 17, no. 5 (2025): 735. https://doi.org/10.3390/rs17050735.

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This paper focuses on the problem of ground-motion target localization tracking and motion state estimation for high-altitude reconnaissance using fixed-wing UAVs. Our goal is to accurately locate and track ground-moving targets and estimate their motion using visible light images, laser measurements of distance, and UAV position and attitude information. Firstly, this paper uses the target detection model of YOLOv8 to obtain the target pixel positions, combined with the measurement data, to establish the geolocalization model of the ground-motion target. Secondly, a motion state estimation al

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7

Popescu, Mihaela, Dennis Mronga, Ivan Bergonzani, Shivesh Kumar, and Frank Kirchner. "Experimental Investigations into Using Motion Capture State Feedback for Real-Time Control of a Humanoid Robot." Sensors 22, no. 24 (2022): 9853. http://dx.doi.org/10.3390/s22249853.

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Regardless of recent advances, humanoid robots still face significant difficulties in performing locomotion tasks. Among the key challenges that must be addressed to achieve robust bipedal locomotion are dynamically consistent motion planning, feedback control, and state estimation of such complex systems. In this paper, we investigate the use of an external motion capture system to provide state feedback to an online whole-body controller. We present experimental results with the humanoid robot RH5 performing two different whole-body motions: squatting with both feet in contact with the groun

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8

Ozawa, Takehiro, Yusuke Sekikawa, and Hideo Saito. "Accuracy and Speed Improvement of Event Camera Motion Estimation Using a Bird’s-Eye View Transformation." Sensors 22, no. 3 (2022): 773. http://dx.doi.org/10.3390/s22030773.

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Event cameras are bio-inspired sensors that have a high dynamic range and temporal resolution. This property enables motion estimation from textures with repeating patterns, which is difficult to achieve with RGB cameras. Therefore, motion estimation of an event camera is expected to be applied to vehicle position estimation. An existing method, called contrast maximization, is one of the methods that can be used for event camera motion estimation by capturing road surfaces. However, contrast maximization tends to fall into a local solution when estimating three-dimensional motion, which makes

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9

Phan, Gia-Hoang, Clint Hansen, Paolo Tommasino, Asif Hussain, Domenico Formica, and Domenico Campolo. "A Complementary Filter Design on SE(3) to Identify Micro-Motions during 3D Motion Tracking." Sensors 20, no. 20 (2020): 5864. http://dx.doi.org/10.3390/s20205864.

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In 3D motion capture, multiple methods have been developed in order to optimize the quality of the captured data. While certain technologies, such as inertial measurement units (IMU), are mostly suitable for 3D orientation estimation at relatively high frequencies, other technologies, such as marker-based motion capture, are more suitable for 3D position estimations at a lower frequency range. In this work, we introduce a complementary filter that complements 3D motion capture data with high-frequency acceleration signals from an IMU. While the local optimization reduces the error of the motio

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10

Jang, Jaeyoung, and Jong Hyeon Park. "A Method of Estimating an Object’s Parameters Based on Simplication with Momentum for a Manipulator." Applied Sciences 15, no. 7 (2025): 3989. https://doi.org/10.3390/app15073989.

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For a manipulator to estimate an object’s inertial parameters—such as mass, center of mass position, and elements of the inertia tensor—it must grasp one side of the object and generate motion while utilizing the resulting forces and torques at its end-effector for estimation. In most previous studies, the estimation motion has involved high acceleration, resulting in larger motion trajectories and increased inertial forces. A larger trajectory raises the risk of collisions, while greater inertial forces could potentially damage the object. This paper introduces an innovative approach that sim

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11

Chen, Yi Wei, and Yung Lung Lee. "An Improved IMM Estimator Combined with Intelligent Input Estimation Technique for Tracking Maneuvering Target." Applied Mechanics and Materials 764-765 (May 2015): 664–70. http://dx.doi.org/10.4028/www.scientific.net/amm.764-765.664.

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The estimation performance of interactive multiple model (IMM) estimator for tracking a maneuvering target is influenced by the target motion models and application of filters. An improved IMM estimation algorithm combined with the intelligent input estimation technique is proposed in this study. The target motion models include the constant velocity (CV) model and the modified Singer acceleration model. The intelligent fuzzy weighted input estimation (IFWIE) is used to compute the acceleration input for the modified Singer acceleration model besides the application of standard Kalman filter (

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12

Schutten, R. J., A. Pelagotti, and G. De Haan. "Layered motion estimation." Philips Journal of Research 51, no. 2 (1998): 253–67. http://dx.doi.org/10.1016/s0165-5817(98)00010-2.

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13

Klomp, Sven, Marco Munderloh, and Jörn Ostermann. "Decoder-Side Motion Estimation Assuming Temporally or Spatially Constant Motion." ISRN Signal Processing 2011 (June 20, 2011): 1–10. http://dx.doi.org/10.5402/2011/956372.

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In current video coding standards, the encoder exploits temporal redundancies within the video sequence by performing block-based motion compensated prediction. However, the motion estimation is only performed at the encoder, and the motion vectors have to be coded explicitly into the bit stream. Recent research has shown that the compression efficiency can be improved by also estimating the motion at the decoder. This paper gives a detailed description of a decoder-side motion estimation architecture which assumes temporal constant motion and compares the proposed motion compensation algorith

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14

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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15

Yaacob, M. S., H. Jamaluddin, and K. C. Wong. "Fuzzy logic approach for estimation of longitudinal aircraft parameters." Aeronautical Journal 106, no. 1065 (2002): 585–94. http://dx.doi.org/10.1017/s0001924000011593.

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AbstractThe use of rule-based fuzzy logic system for estimating the stability and control derivatives for the longitudinal aircraft motion is proposed. The capabilities of the fuzzy logic system in estimating both the short-period and the phugoid mode of motions are explored. The flight data used in the estimation process were generated using the three nonlinear longitudinal equation of motion for a small remotely piloted vehicle with all the aerodynamic coefficients obtained from the wind-tunnel tests. The preferred method of perturbation of the aircraft elevator for data collection is also h

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16

Yaacob, M. S., H. Jamaluddin, and K. C. Wong. "Fuzzy logic approach for estimation of longitudinal aircraft parameters." Aeronautical Journal 106, no. 1065 (2002): 585–94. http://dx.doi.org/10.1017/s0001924000018248.

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AbstractThe use of rule-based fuzzy logic system for estimating the stability and control derivatives for the longitudinal aircraft motion is proposed. The capabilities of the fuzzy logic system in estimating both the short-period and the phugoid mode of motions are explored. The flight data used in the estimation process were generated using the three nonlinear longitudinal equation of motion for a small remotely piloted vehicle with all the aerodynamic coefficients obtained from the wind-tunnel tests. The preferred method of perturbation of the aircraft elevator for data collection is also h

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17

Gutierrez, Hector, and Dengfeng Li. "Nonlinear Passive Observer for Motion Estimation in Multi-Axis Precision Motion Control." Machines 12, no. 6 (2024): 376. http://dx.doi.org/10.3390/machines12060376.

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A nonlinear passive observer (NPO) for estimating the time-varying velocity vector of a multi-axis high-precision motion control stage is presented. The proposed nonlinear estimation strategy is developed based on a Lyapunov stability analysis, which proves that the NPO is stable. Three test cases are used to investigate the performance of the proposed observer. Experimental results are given to demonstrate the performance of the proposed NPO in accurately estimating time-varying velocity during alignment, reciprocating motion, and multi-axis motion in high-precision motion control application

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18

R, Vinothkanna. "A Survey on Novel Estimation Approach of Motion Controllers for Self-Driving Cars." December 2020 2, no. 4 (2021): 211–19. http://dx.doi.org/10.36548/jei.2020.4.003.

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The motion planning framework is one of the challenging tasks in autonomous driving cars. During motion planning, predicting of trajectory is computed by Gaussian propagation. Recently, the localization uncertainty control will be estimating by Gaussian framework. This estimation suffers from real time constraint distribution for (Global Positioning System) GPS error. In this research article compared novel motion planning methods and concluding the suitable estimating algorithm depends on the two different real time traffic conditions. One is the realistic unusual traffic and complex target i

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19

Deesomsuk, Teerachai, and Tospol Pinkaew. "Effectiveness of Vehicle Weight Estimation from Bridge Weigh-in-Motion." Advances in Civil Engineering 2009 (2009): 1–13. http://dx.doi.org/10.1155/2009/312034.

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The effectiveness of vehicle weight estimations from bridge weigh-in-motion system is studied. The measured bending moments of the instrumented bridge under a passage of vehicle are numerically simulated and are used as the input for the vehicle weight estimations. Two weight estimation methods assuming constant magnitudes and time-varying magnitudes of vehicle axle loads are investigated. The appropriate number of bridge elements and sampling frequency are considered. The effectiveness in term of the estimation accuracy is evaluated and compared under various parameters of vehicle-bridge syst

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20

Chauvet, Antoine, Yoshihiro Sugaya, Tomo Miyazaki, and Shinichiro Omachi. "Optical Flow-Based Fast Motion Parameters Estimation for Affine Motion Compensation." Applied Sciences 10, no. 2 (2020): 729. http://dx.doi.org/10.3390/app10020729.

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This study proposes a lightweight solution to estimate affine parameters in affine motion compensation. Most of the current approaches start with an initial approximation based on the standard motion estimation, which only estimates the translation parameters. From there, iterative methods are used to find the best parameters, but they require a significant amount of time. The proposed method aims to speed up the process in two ways, first, skip evaluating affine prediction when it is likely to bring no encoding efficiency benefit, and second, by estimating better initial values for the iterat

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21

Lehtonen, Eero, Jarmo Teuho, Juho Koskinen, et al. "A Respiratory Motion Estimation Method Based on Inertial Measurement Units for Gated Positron Emission Tomography." Sensors 21, no. 12 (2021): 3983. http://dx.doi.org/10.3390/s21123983.

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We present a novel method for estimating respiratory motion using inertial measurement units (IMUs) based on microelectromechanical systems (MEMS) technology. As an application of the method we consider the amplitude gating of positron emission tomography (PET) imaging, and compare the method against a clinically used respiration motion estimation technique. The presented method can be used to detect respiratory cycles and estimate their lengths with state-of-the-art accuracy when compared to other IMU-based methods, and is the first based on commercial MEMS devices, which can estimate quantit

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22

Weber, Daniel, Clemens Gühmann, and Thomas Seel. "RIANN—A Robust Neural Network Outperforms Attitude Estimation Filters." AI 2, no. 3 (2021): 444–63. http://dx.doi.org/10.3390/ai2030028.

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Inertial-sensor-based attitude estimation is a crucial technology in various applications, from human motion tracking to autonomous aerial and ground vehicles. Application scenarios differ in characteristics of the performed motion, presence of disturbances, and environmental conditions. Since state-of-the-art attitude estimators do not generalize well over these characteristics, their parameters must be tuned for the individual motion characteristics and circumstances. We propose RIANN, a ready-to-use, neural network-based, parameter-free, real-time-capable inertial attitude estimator, which

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23

Bellers, E. B., and G. de Haan. "Advanced Motion Estimation and Motion Compensated Deinterlacing." SMPTE Journal 106, no. 11 (1997): 777–86. http://dx.doi.org/10.5594/j17643.

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24

Hosur, P. I. "Motion adaptive search for fast motion estimation." IEEE Transactions on Consumer Electronics 49, no. 4 (2003): 1330–40. http://dx.doi.org/10.1109/tce.2003.1261237.

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25

Gupta, Naresh C., and Laveen N. Kanal. "3-D motion estimation from motion field." Artificial Intelligence 78, no. 1-2 (1995): 45–86. http://dx.doi.org/10.1016/0004-3702(95)00031-3.

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26

Ou, Gwo-Bin, and Robert B. Herrmann. "Estimation Theory for Peak Ground Motion." Seismological Research Letters 61, no. 2 (1990): 99–107. http://dx.doi.org/10.1785/gssrl.61.2.99.

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Abstract The application of estimation theory for predicting peak ground motion is critically examined in order to be more precise in its application. Estimation theory relates peak ground motion to the duration and spectrum of the signal. Using vertical component data from the Eastern Canada Telemetered Network, at distance range of 100–1000 km, we find that a duration must be defined by the interval where the cumulative energy of the main signal increases linearly, here between 5% and 75% of the cumulative power. This duration, when used with the spectra within this window, adequately replic

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27

Otsuka, Taku, and Yuko Yotsumoto. "Partially Separable Aspects of Spatial and Temporal Estimations in Virtual Navigation as Revealed by Adaptation." i-Perception 13, no. 1 (2022): 204166952210788. http://dx.doi.org/10.1177/20416695221078878.

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Recent studies claim that estimating the magnitude of the spatial and temporal aspects of one's self-motion shows similar characteristics, suggesting shared processing mechanisms between these two dimensions. While the estimation of other magnitude dimensions, such as size, number, and duration, exhibits negative aftereffects after prolonged exposure to the stimulus, it remains to be elucidated whether this could occur similarly in the estimation of the distance travelled and time elapsed during one's self-motion. We sought to fill this gap by examining the effects of adaptation on distance an

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28

B.Chaitanya E, B. Chaitanya E., and A. Mohan E. A.Mohan E. "An EDDR Architecture for Motion Estimation Testing Applications." International Journal of Scientific Research 1, no. 7 (2012): 73–75. http://dx.doi.org/10.15373/22778179/dec2012/29.

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29

Zhao, Jijun, Lishuang Liu, Zhongcheng Wei, Chunhua Zhang, Wei Wang, and Yongjian Fan. "R-DEHM: CSI-Based Robust Duration Estimation of Human Motion with WiFi." Sensors 19, no. 6 (2019): 1421. http://dx.doi.org/10.3390/s19061421.

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As wireless sensing has developed, wireless behavior recognition has become a promising research area, in which human motion duration is one of the basic and significant parameters to measure human behavior. At present, however, there is no consideration of the duration estimation of human motion leveraging wireless signals. In this paper, we propose a novel system for robust duration estimation of human motion (R-DEHM) with WiFi in the area of interest. To achieve this, we first collect channel statement information (CSI) measurements on commodity WiFi devices and extract robust features from

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30

Chen, Haiwen, Jin Chen, Zhuohuai Guan, Yaoming Li, Kai Cheng, and Zhihong Cui. "Stereovision-Based Ego-Motion Estimation for Combine Harvesters." Sensors 22, no. 17 (2022): 6394. http://dx.doi.org/10.3390/s22176394.

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Ego-motion estimation is a foundational capability for autonomous combine harvesters, supporting high-level functions such as navigation and harvesting. This paper presents a novel approach for estimating the motion of a combine harvester from a sequence of stereo images. The proposed method starts with tracking a set of 3D landmarks which are triangulated from stereo-matched features. Six Degree of Freedom (DoF) ego motion is obtained by minimizing the reprojection error of those landmarks on the current frame. Then, local bundle adjustment is performed to refine structure (i.e., landmark pos

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31

Ma, Chao, Chun Jie Qiao, Yue Ke Wang, and Shen Zhao. "A New Method for Target Motion Analysis." Applied Mechanics and Materials 336-338 (July 2013): 2354–58. http://dx.doi.org/10.4028/www.scientific.net/amm.336-338.2354.

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The paper proposes a new method for a targets trajectory, assumed to be linear and uniform, based on the observation of its speed and bearings. After introducing the new method based on assumed model, the paper analyzes the relative error of range estimation caused by speed and bearings estimations relative error; The results of target motion analysis (TMA) is optimized by linearizing the model and using kalman filter. Pond test shows that relative error of range estimation calculated by this method is less than 10-1.

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32

Davydova, Nadezhda, Dmitry Lukashevich, Dmitry Bykov, et al. "AMPLITUDE-TIME ANALYSIS OF BIOMECHANICAL PATTERNS OF HUMAN MOTIONS." Journal of Engineering Science XXVII (3) (September 15, 2020): 169–81. https://doi.org/10.5281/zenodo.3949690.

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Biomechanical analysis of motions solves the tasks of efficiency estimation of movement realization, search of technique optimal variants and tactics of motion performance, definition of a degree and reasons of not matching real movement action to optimal one. Today, inertial measurement devices based on microelectromechanical sensors (MEMS) are becoming more and more popular for biomechanical analysis of human motions. The paper describes an algorithm for estimation of the biomechanical pattern of human motions based on amplitude-time analysis of inertial gyroscope signals. The presented algo

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33

Orchard, Garrick, and Ralph Etienne-Cummings. "Bioinspired Visual Motion Estimation." Proceedings of the IEEE 102, no. 10 (2014): 1520–36. http://dx.doi.org/10.1109/jproc.2014.2346763.

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Pérez-Rúa, Juan-Manuel, Tomas Crivelli, and Patrick Pérez. "Object-guided motion estimation." Computer Vision and Image Understanding 153 (December 2016): 88–99. http://dx.doi.org/10.1016/j.cviu.2016.05.005.

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Tian, Tina Yu, and Mubarak Shah. "Motion estimation and segmentation." Machine Vision and Applications 9, no. 1 (1996): 32–42. http://dx.doi.org/10.1007/bf01246637.

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Koc, U. V., and K. J. Ray Liu. "DCT-based motion estimation." IEEE Transactions on Image Processing 7, no. 7 (1998): 948–65. http://dx.doi.org/10.1109/83.701146.

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Sworder, D. D., and J. E. Boyd. "Improved motion-mode estimation." IEEE Transactions on Aerospace and Electronic Systems 41, no. 3 (2005): 1052–56. http://dx.doi.org/10.1109/taes.2005.1541449.

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Choi, Sun-Young, Soo-Ik Chae, and Young Serk Shim. "Rate-optimised motion estimation." Electronics Letters 36, no. 14 (2000): 1196. http://dx.doi.org/10.1049/el:20000874.

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Tian, Tina Yu, and Mubarak Shah. "Motion estimation and segmentation." Machine Vision and Applications 9, no. 1 (1996): 32–42. http://dx.doi.org/10.1007/s001380050026.

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Ding, Jia-rui, Zhong-jian Li, and Jin-wen An. "Robust global motion estimation." Optoelectronics Letters 3, no. 4 (2007): 303–7. http://dx.doi.org/10.1007/s11801-007-6171-7.

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Pan, Zhaoqing, Jianjun Lei, Yajuan Zhang, and Fu Lee Wang. "Adaptive Fractional-Pixel Motion Estimation Skipped Algorithm for Efficient HEVC Motion Estimation." ACM Transactions on Multimedia Computing, Communications, and Applications 14, no. 1 (2018): 1–19. http://dx.doi.org/10.1145/3159170.

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Park, Chun-Su. "Level-set-based motion estimation algorithm for multiple reference frame motion estimation." Journal of Visual Communication and Image Representation 24, no. 8 (2013): 1269–75. http://dx.doi.org/10.1016/j.jvcir.2013.08.008.

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Roda-Sales, Alba, Joaquín L. Sancho-Bru, and Margarita Vergara. "Studying kinematic linkage of finger joints: estimation of kinematics of distal interphalangeal joints during manipulation." PeerJ 10 (October 4, 2022): e14051. http://dx.doi.org/10.7717/peerj.14051.

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The recording of hand kinematics during product manipulation is challenging, and certain degrees of freedom such as distal interphalangeal (DIP) joints are difficult to record owing to limitations of the motion capture systems used. DIP joint kinematics could be estimated by taking advantage of its kinematic linkage with proximal interphalangeal (PIP) and metacarpophalangeal joints. This work analyses this linkage both in free motion conditions and during the performance of 26 activities of daily living. We have studied the appropriateness of different types of linear regressions (several comb

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Zhang, Qinghui, Junqiu Li, Zhenping Qiang, and Libo He. "A Preprocess Method of External Disturbance Suppression for Carotid Wall Motion Estimation Using Local Phase and Orientation of B-Mode Ultrasound Sequences." BioMed Research International 2019 (November 21, 2019): 1–15. http://dx.doi.org/10.1155/2019/6547982.

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Estimating the motions of the common carotid artery wall plays a very important role in early diagnosis of the carotid atherosclerotic disease. However, the disturbances caused by either the instability of the probe operator or the breathing of subjects degrade the estimation accuracy of arterial wall motion when performing speckle tracking on the B-mode ultrasound images. In this paper, we propose a global registration method to suppress external disturbances before motion estimation. The local vector images, transformed from B-mode images, were used for registration. To take advantage of bot

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Hu, Juqi, Subhash Rakheja, and Youmin Zhang. "Tire–road friction coefficient estimation based on designed braking pressure pulse." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 235, no. 7 (2021): 1876–91. http://dx.doi.org/10.1177/0954407020983580.

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Knowledge of tire–road friction coefficient (TRFC) is valuable for autonomous vehicle control and design of active safety systems. This paper investigates TRFC estimation on the basis of longitudinal vehicle dynamics. A two-stage TRFC estimation scheme is proposed that limits the disturbances to the vehicle motion. A sequence of braking pressure pulses is designed in the first stage to identify desired minimal pulse pressure for reliable estimation of TRFC with minimal interference with the vehicle motion. This stage also provides a qualitative estimate of TRFC. In the second stage, tire norma

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Choi, Young-Ju, Dong-San Jun, Won-Sik Cheong, and Byung-Gyu Kim. "Design of Efficient Perspective Affine Motion Estimation/Compensation for Versatile Video Coding (VVC) Standard." Electronics 8, no. 9 (2019): 993. http://dx.doi.org/10.3390/electronics8090993.

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The fundamental motion model of the conventional block-based motion compensation in High Efficiency Video Coding (HEVC) is a translational motion model. However, in the real world, the motion of an object exists in the form of combining many kinds of motions. In Versatile Video Coding (VVC), a block-based 4-parameter and 6-parameter affine motion compensation (AMC) is being applied. In natural videos, in the majority of cases, a rigid object moves without any regularity rather than maintains the shape or transform with a certain rate. For this reason, the AMC still has a limit to compute compl

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Alvarez, Juan, Diego Álvarez, and Antonio López. "Accelerometry-Based Distance Estimation for Ambulatory Human Motion Analysis." Sensors 18, no. 12 (2018): 4441. http://dx.doi.org/10.3390/s18124441.

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In human motion science, accelerometers are used as linear distance sensors by attaching them to moving body parts, with their measurement axes its measurement axis aligned in the direction of motion. When double integrating the raw sensor data, multiple error sources are also integrated integrated as well, producing inaccuracies in the final position estimation which increases fast with the integration time. In this paper, we make a systematic and experimental comparison of different methods for position estimation, with different sensors and in different motion conditions. The objective is t

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KRAMER, KATHLEEN A., and STEPHEN C. STUBBERUD. "ANALYSIS AND IMPLEMENTATION OF A NEURAL EXTENDED KALMAN FILTER FOR TARGET TRACKING." International Journal of Neural Systems 16, no. 01 (2006): 1–13. http://dx.doi.org/10.1142/s0129065706000457.

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Having a better motion model in the state estimator is one way to improve target tracking performance. Since the motion model of the target is not known a priori, either robust modeling techniques or adaptive modeling techniques are required. The neural extended Kalman filter is a technique that learns unmodeled dynamics while performing state estimation in the feedback loop of a control system. This coupled system performs the standard estimation of the states of the plant while estimating a function to approximate the difference between the given state-coupling function model and the behavio

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Chen, Shengyang. "Motion estimation algorithm and architecture survey." Applied and Computational Engineering 6, no. 1 (2023): 505–13. http://dx.doi.org/10.54254/2755-2721/6/20230847.

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Motion estimation is a key part of video temporal characteristics analysis including video filter and compression. Increasing requirements for high-quality video image processing have confirmed the necessity of researching motion estimation. Current motion estimation methods, including high-efficient fast motion estimation algorithms and hardware architecture designs, achieved different performances from different perspectives. In this paper, we focus on analyzing typical fast algorithms and hardware architecture designs for motion estimation, comparing the used methods, and pointing out the b

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Kim, Ji-Hye, Thi Loan Mai, Aeri Cho, et al. "Establishment of a Pressure Variation Model for the State Estimation of an Underwater Vehicle." Applied Sciences 14, no. 3 (2024): 970. http://dx.doi.org/10.3390/app14030970.

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This study presents a pressure variation model (PVM) derived from the regression analysis of dynamic pressure computed through numerical analysis to estimate the velocity of underwater vehicles. Furthermore, the drift angle estimation algorithm was developed using predicted velocities from PVM and pressure sensor differences. This approach estimates the single-motion states of underwater vehicles, such as straight, turning, and gliding. Furthermore, it confirms the viability of state estimation even in multiple motions involving turning and gliding motion with a drift angle and spiral motion.

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