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Journal articles on the topic 'Motion data'

Author: Grafiati

Published: 23 June 2021

Last updated: 29 July 2025

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1

Lv, Na, Yan Huang, Zhi Quan Feng, and Jing Liang Peng. "A Survey on Motion Capture Data Retrieval." Applied Mechanics and Materials 556-562 (May 2014): 2944–47. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.2944.

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With the rapid development of motion capture technology, large motion capture databases are established. How to effectively retrieve the motions from huge amounts of motion data has become a hot topic in computer animation. In this paper, we give a survey on current motion capture data retrieval methods and point out some still existing problems at the end.

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Dong, Ran, Dongsheng Cai, and Soichiro Ikuno. "Motion Capture Data Analysis in the Instantaneous Frequency-Domain Using Hilbert-Huang Transform." Sensors 20, no. 22 (2020): 6534. http://dx.doi.org/10.3390/s20226534.

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Motion capture data are widely used in different research fields such as medical, entertainment, and industry. However, most motion researches using motion capture data are carried out in the time-domain. To understand human motion complexities, it is necessary to analyze motion data in the frequency-domain. In this paper, to analyze human motions, we present a framework to transform motions into the instantaneous frequency-domain using the Hilbert-Huang transform (HHT). The empirical mode decomposition (EMD) that is a part of HHT decomposes nonstationary and nonlinear signals captured from th

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Trivedi, Urvish, Redwan Alqasemi, and Rajiv Dubey. "CARRT—Motion Capture Data for Robotic Human Upper Body Model." Sensors 23, no. 20 (2023): 8354. http://dx.doi.org/10.3390/s23208354.

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In recent years, researchers have focused on analyzing humans’ daily living activities to study various performance metrics that humans subconsciously optimize while performing a particular task. In order to recreate these motions in robotic structures based on the human model, researchers developed a framework for robot motion planning which is able to use various optimization methods to replicate similar motions demonstrated by humans. As part of this process, it will be necessary to record the motions data of the human body and the objects involved in order to provide all the essential info

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Chiu, H. C., F. J. Wu, C. J. Lin, H. C. Huang, and C. C. Liu. "Effects of rotation motions on strong-motion data." Journal of Seismology 16, no. 4 (2012): 829–38. http://dx.doi.org/10.1007/s10950-012-9301-z.

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Et.al, JIBUM JUNG. "Use of Human Motion Data to Train Wearable Robots." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 6 (2021): 807–11. http://dx.doi.org/10.17762/turcomat.v12i6.2100.

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Development of wearable robots is accelerating. Walking robots mimic human behavior and must operate without accidents. Human motion data are needed to train these robots. We developed a system for extracting human motion data and displaying them graphically.We extracted motion data using a Perception Neuron motion capture system and used the Unity engine for the simulation. Several experiments were performed to demonstrate the accuracy of the extracted motion data.Of the various methods used to collect human motion data, markerless motion capture is highly inaccurate, while optical motion cap

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Yong-Qiong Zhu, Yong-Qiong Zhu, Ye-Ming Cai Yong-Qiong Zhu, and Fan Zhang Ye-Ming Cai. "Motion Capture Data Denoising Based on LSTNet Autoencoder." 網際網路技術學刊 23, no. 1 (2022): 011–20. http://dx.doi.org/10.53106/160792642022012301002.

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<p>This paper proposes a novel deep learning-based optical motion capture denoising model encoder-LSTNet- decoder (ELD). ELD uses an autoencoder for manifold learning and decoder to remove jitter noise and missing noise effectively. It uses recurrent units in LSTNet to effectively obtain the spatial-temporal information of motion sequences, especially the periodic long-term and short-term features. In the denoising procedure, the kinetical characteristics of the motion are also considered so that the reconstructed deviation is smaller and can more accurately reflect the real action. We s

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Manns, Martin, Michael Otto, and Markus Mauer. "Measuring Motion Capture Data Quality for Data Driven Human Motion Synthesis." Procedia CIRP 41 (2016): 945–50. http://dx.doi.org/10.1016/j.procir.2015.12.068.

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Li, Bo, Chao Zhang, Cheng Han, and Baoxing Bai. "Gesture Recognition Based on Kinect v2 and Leap Motion Data Fusion." International Journal of Pattern Recognition and Artificial Intelligence 33, no. 05 (2019): 1955005. http://dx.doi.org/10.1142/s021800141955005x.

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This study proposed a method for multiple motion-sensitive devices (i.e. one Kinect v2 and two Leap Motions) to integrate gesture data in Unity. Other depth cameras could replace the Kinect. The general steps in integrating gesture data for motion-sensitive devices were introduced as follows. (1) A method was proposed to recognize the fingertip from depth images for the Kinect v2. (2) Coordinates observed by three motion-sensitive devices were aligned in space in three steps. First, preliminary coordinate conversion parameters were obtained through joint calibration of the three devices. Secon

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I-Chen Lin, Jen-Yu Peng, Chao-Chih Lin, and Ming-Han Tsai. "Adaptive Motion Data Representation with Repeated Motion Analysis." IEEE Transactions on Visualization and Computer Graphics 17, no. 4 (2011): 527–38. http://dx.doi.org/10.1109/tvcg.2010.87.

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Wang, Xiaoting, Xiangxu Meng, Chenglei Yang, and Junqing Zhang. "Data Driven Avatars Roaming in Digital Museum." International Journal of Virtual Reality 8, no. 3 (2009): 13–18. http://dx.doi.org/10.20870/ijvr.2009.8.3.2736.

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This paper describes a motion capture (mocap) data-driven digital museum roaming system with high walking reality. We focus on three main questions: the animation of avatars; the path planning; and the collision detection among avatars. We use only a few walking clips from mocap data to synthesize walking motions with natural transitions, any direction and any length. Let the avatars roam in the digital museum with its Voronoi skeleton path, shortest path or offset path. And also we use Voronoi diagram to do collision detection. Different users can set up their own avatars and roam along their

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Wei, Xiaopeng, Boxiang Xiao, and Qiang Zhang. "A retrieval method for human Mocap data based on biomimetic pattern recognition." Computer Science and Information Systems 7, no. 1 (2010): 99–109. http://dx.doi.org/10.2298/csis1001099w.

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A retrieval method for human Mocap (Motion Capture) data based on biomimetic pattern recognition is presented in this paper. BVH rotation channels are extracted as features of motion for both the retrieval instance and the motion data. Several hyper sausage neurons are constructed according to the retrieval instance, and the trained domain covered by these hyper sausage neurons can be considered as the distribution range of a same kind of motions. By use of CMU free motion database, the retrieval algorithm has been implemented and examined, and the experimental results are illustrated. At the

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Odagiri, Hayato, Hiroshi Watabe, Kentaro Takanami, et al. "Verification of the effect of data-driven brain motion correction on PET imaging." PLOS ONE 19, no. 7 (2024): e0301919. http://dx.doi.org/10.1371/journal.pone.0301919.

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Introduction Brain positron emission tomography/computed tomography (PET/CT) scans are useful for identifying the cause of dementia by evaluating glucose metabolism in the brain with F-18-fluorodeoxyglucose or Aβ deposition with F-18-florbetaben. However, since imaging time ranges from 10 to 30 minutes, movements during the examination might result in image artifacts, which interfere with diagnosis. To solve this problem, data-driven brain motion correction (DDBMC) techniques are capable of performing motion corrected reconstruction using highly accurate motion estimates with high temporal res

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Spratt, D. "SP-0030 Against the motion: Data, data, data." Radiotherapy and Oncology 158 (May 2021): S20. http://dx.doi.org/10.1016/s0167-8140(21)06470-7.

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Ebel, John E., and David J. Wald. "Bayesian Estimations of Peak Ground Acceleration and 5% Damped Spectral Acceleration from Modified Mercalli Intensity Data." Earthquake Spectra 19, no. 3 (2003): 511–29. http://dx.doi.org/10.1193/1.1596549.

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We describe a new probabilistic method that uses observations of modified Mercalli intensity (MMI) from past earthquakes to make quantitative estimates of ground shaking parameters (i.e., peak ground acceleration, peak ground velocity, 5% damped spectral acceleration values, etc.). The method uses a Bayesian approach to make quantitative estimates of the probabilities of different levels of ground motions from intensity data given an earthquake of known location and magnitude. The method utilizes probability distributions from an intensity/ground motion data set along with a ground motion atte

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YAMANE, KATSU, JESSICA K. HODGINS, and H. BENJAMIN BROWN. "CONTROLLING A MOTORIZED MARIONETTE WITH HUMAN MOTION CAPTURE DATA." International Journal of Humanoid Robotics 01, no. 04 (2004): 651–69. http://dx.doi.org/10.1142/s0219843604000319.

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In this paper, we present a method for controlling a motorized, string-driven marionette using motion capture data from human actors and from a traditional marionette operated by a professional puppeteer. We are interested in using motion capture data of a human actor to control the motorized marionette as a way of easily creating new performances. We use data from the hand-operated marionette both as a way of assessing the performance of the motorized marionette and to explore whether this technology could be used to preserve marionette performances. The human motion data must be extensively

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Kashima, T. "Characteristics of Ground Motions and Strong Motion Data of Buildings." Concrete Journal 50, no. 1 (2012): 19–22. http://dx.doi.org/10.3151/coj.50.19.

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Panzhin, Andrei, and Nataliia Panzhina. "Applying primary data from permanent stations for geodynamic zoning." Izvestiya vysshikh uchebnykh zavedenii. Gornyi zhurnal, no. 1 (February 17, 2021): 54–62. http://dx.doi.org/10.21440/0536-1028-2021-1-54-62.

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Introduction. The article focuses on present-day geodynamic motion in order to carry out geodynamic zoning of territories. Geodynamic monitoring may be both regional, for instance, of the Russian Federation, Ural region, geological rock mass, and it may also be local, i.e. covering a deposit and enclosing rock mass. Permanent stations of Global Navigation Satellite System (GNSS) have been used as a source of data for deformation monitoring. Methodology included the method of visualizing geodynamic motions according to the results of cyclic geodetic measurements which makes it possible to singl

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Southwick, Matthew, Zhu Mao, and Christopher Niezrecki. "Volumetric Motion Magnification: Subtle Motion Extraction from 4D Data." Measurement 176 (May 2021): 109211. http://dx.doi.org/10.1016/j.measurement.2021.109211.

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Miura, Takeshi, Takaaki Kaiga, Naho Matsumoto, et al. "Characterization of Motion Capture Data by Motion Speed Variation." IEEJ Transactions on Electronics, Information and Systems 133, no. 4 (2013): 906–7. http://dx.doi.org/10.1541/ieejeiss.133.906.

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Choi, Myung Geol, and Taesoo Kwon. "Motion rank: applying page rank to motion data search." Visual Computer 35, no. 2 (2018): 289–300. http://dx.doi.org/10.1007/s00371-018-1498-6.

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Zega, Selly Artaty, Ahmad Saropi, Timothy Ronaldy, Yogi Ilhami, and Muhammad Farabi. "Mengatasi Data Error Pada Proses Data Cleaning Motion Capture Motive Optitrack." JOURNAL OF APPLIED MULTIMEDIA AND NETWORKING 6, no. 1 (2022): 89–94. http://dx.doi.org/10.30871/jamn.v6i1.4210.

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Motion capture adalah sebuah teknologi dalam industri multimedia yang berguna untuk merekam gerakan secara digital dengan menggunakan metode sensor.Teknologi motion capture semakin berkembang dari waktu ke waktu, motion capture sudah digunakan di beberapa produk digital seperti game, efek visual, dan film animasi.pada proses perekaman gerakan, motion capture menggunakan sensor optik atau sensor magnet, langkah selanjutnya adalah proses pembersihan data.proses pembersihan data akan membersihkan noise atau kesalahan gerakan. Menggunakan motion capture akan membuat proses produksi lebih cepat kar

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22

Cousins, Jim, and Graeme H. McVerry. "Overview of strong-motion data from the Darfield earthquake." Bulletin of the New Zealand Society for Earthquake Engineering 43, no. 4 (2010): 222–27. http://dx.doi.org/10.5459/bnzsee.43.4.222-227.

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The Darfield earthquake of 3rd September 2010 UT and its aftershocks have yielded New Zealand’s richest set of strong-motion data since recording began in the early 1960s. Main-shock accelerograms were returned by 130 sites, ten of which had peak horizontal accelerations in the range 0.3 to 0.82g. One near-fault record, from Greendale, had a peak vertical acceleration of 1.26g. Eighteen records showed peak ground velocities exceeding 0.5 m/s, with three of them exceeding 1 m/s. The records included some with strong long-period directivity pulses, some with other long-period components that wer

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Li, Hai, Hwa Jen Yap, and Selina Khoo. "Motion Classification and Features Recognition of a Traditional Chinese Sport (Baduanjin) Using Sampled-Based Methods." Applied Sciences 11, no. 16 (2021): 7630. http://dx.doi.org/10.3390/app11167630.

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This study recognized the motions and assessed the motion accuracy of a traditional Chinese sport (Baduanjin), using the data from the inertial sensor measurement system (IMU) and sampled-based methods. Fifty-three participants were recruited in two batches to participate in the study. Motion data of participants practicing Baduanjin were captured by IMU. By extracting features from motion data and benchmarking with the teacher’s assessment of motion accuracy, this study verifies the effectiveness of assessment on different classifiers for motion accuracy of Baduanjin. Moreover, based on the e

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Mi, Jian, and Yasutake Takahashi. "Humanoid Robot Motion Modeling Based on Time-Series Data Using Kernel PCA and Gaussian Process Dynamical Models." Journal of Advanced Computational Intelligence and Intelligent Informatics 22, no. 6 (2018): 965–77. http://dx.doi.org/10.20965/jaciii.2018.p0965.

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In this article, contrary to popular studies on human motion learning, we focus on addressing the problem of humanoid robot motions directly. Performances of different kernel functions with principal components analysis (PCA) in Gaussian process dynamical models (GPDM) are investigated to build efficient humanoid robot motion models. A novel kernel-PCA-GPDM method is proposed for building different types of humanoid robot motion models. Compared with the standard-PCA-GPDM and auto-encoder-GPDM methods, our proposed method is more efficient in humanoid robot motion modeling. In this work, three

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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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Ozturk, C., J. A. Derbyshire, and E. R. McVeigh. "Estimating motion from MRI data." Proceedings of the IEEE 91, no. 10 (2003): 1627–48. http://dx.doi.org/10.1109/jproc.2003.817872.

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Riaz, Qaiser, Björn Krüger, and Andreas Weber. "Relational databases for motion data." International Journal of Innovative Computing and Applications 7, no. 3 (2016): 119. http://dx.doi.org/10.1504/ijica.2016.078723.

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Lee, W. H. K., and T. C. Shin. "Strong-Motion Instrumentation and Data." Earthquake Spectra 17, no. 1_suppl (2001): 5–18. http://dx.doi.org/10.1193/1.1586190.

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Benický, Peter, and Ladislav Jurišica. "Real Time Motion Data Preprocessing." Journal of Electrical Engineering 61, no. 4 (2010): 247–51. http://dx.doi.org/10.2478/v10187-010-0035-2.

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Real Time Motion Data PreprocessingThere is a lot of redundant data for image processing in an image, in motion picture as well. The more data for image processing we have, the more time is needed for preprocessing it. That is why we need to work with important data only. In order to identify or classify motion, data processing in real time is needed.

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L., Jagath J., Shalij P. R, and Haris Naduthodi. "Motion Picture Data Management System." International Journal of Business Innovation and Research 1, no. 1 (2020): 1. http://dx.doi.org/10.1504/ijbir.2020.10034213.

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Bae, Tae Young, and Young Seog Kim. "Generation and Animation of Optimal Robot Joint Motion data using Captured Human Motion data." Journal of manufacturing engineering & technology 22, no. 3_1spc (2013): 558–65. http://dx.doi.org/10.7735/ksmte.2013.22.3.558.

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32

Li, Hai, Selina Khoo, and Hwa Jen Yap. "Implementation of Sequence-Based Classification Methods for Motion Assessment and Recognition in a Traditional Chinese Sport (Baduanjin)." International Journal of Environmental Research and Public Health 19, no. 3 (2022): 1744. http://dx.doi.org/10.3390/ijerph19031744.

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This study aimed to assess the motion accuracy of Baduanjin and recognise the motions of Baduanjin based on sequence-based methods. Motion data of Baduanjin were measured by the inertial sensor measurement system (IMU). Fifty-four participants were recruited to capture motion data. Based on the motion data, various sequence-based methods, namely dynamic time warping (DTW) combined with classifiers, hidden Markov model (HMM), and recurrent neural networks (RNNs), were applied to assess motion accuracy and recognise the motions of Baduanjin. To assess motion accuracy, the scores for motion accur

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Akber, Syed Muhammad Abrar, Sadia Nishat Kazmi, Syed Muhammad Mohsin, and Agnieszka Szczęsna. "Deep Learning-Based Motion Style Transfer Tools, Techniques and Future Challenges." Sensors 23, no. 5 (2023): 2597. http://dx.doi.org/10.3390/s23052597.

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In the fourth industrial revolution, the scale of execution for interactive applications increased substantially. These interactive and animated applications are human-centric, and the representation of human motion is unavoidable, making the representation of human motions ubiquitous. Animators strive to computationally process human motion in a way that the motions appear realistic in animated applications. Motion style transfer is an attractive technique that is widely used to create realistic motions in near real-time. motion style transfer approach employs existing captured motion data to

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Wielen, Roland. "A Comprehensive Astrometric Data Base: An Instrument for Combining Earth-Bound Observations With Hipparcos Data." Symposium - International Astronomical Union 141 (1990): 483–88. http://dx.doi.org/10.1017/s0074180900087386.

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The astrometric data bank ARIGFH will contain all relevant astrometric data on stellar positions and proper motions of stars from ground-based observations and space missions. For each star in the ARIGFH, the best available position and proper motion shall be derived. We rediscuss the accuracy of proper motions and positions of fundamental stars, resulting from a combination of data in the FK5 with the expected results from a revised HIPPARCOS mission. The FK5 data could be significantly improved even by rather degraded positions from a revised HIPPARCOS mission.

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Li, Peizhuo, Kfir Aberman, Zihan Zhang, Rana Hanocka, and Olga Sorkine-Hornung. "GANimator." ACM Transactions on Graphics 41, no. 4 (2022): 1–12. http://dx.doi.org/10.1145/3528223.3530157.

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We present GANimator, a generative model that learns to synthesize novel motions from a single, short motion sequence. GANimator generates motions that resemble the core elements of the original motion, while simultaneously synthesizing novel and diverse movements. Existing data-driven techniques for motion synthesis require a large motion dataset which contains the desired and specific skeletal structure. By contrast, GANimator only requires training on a single motion sequence, enabling novel motion synthesis for a variety of skeletal structures e.g. , bipeds, quadropeds, hexapeds, and more.

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Etemadpour, Ronak, and Angus Graeme Forbes. "Density-based motion." Information Visualization 16, no. 1 (2016): 3–20. http://dx.doi.org/10.1177/1473871615606187.

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A common strategy for encoding multidimensional data for visual analysis is to use dimensionality reduction techniques that project data from higher dimensions onto a lower-dimensional space. This article examines the use of motion to retain an accurate representation of the point density of clusters that might otherwise be lost when a multidimensional dataset is projected into a two-dimensional space. Specifically, we consider different types of density-based motion, where the magnitude of the motion is directly related to the density of the clusters. We investigate how users interpret motion

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Zhang, Xintian, Wenjun Xie, Shujie Li, and Xiaoping Liu. "Convolutional Neural Networks Based Motion Data Optimization Networks forLeap Motion." Journal of Computer-Aided Design & Computer Graphics 33, no. 3 (2021): 439–47. http://dx.doi.org/10.3724/sp.j.1089.2021.18425.

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Igarashi, Ko, and Seiichiro Katsura. "Motion-Data Processing and Reproduction Based on Motion-Copying System." IEEJ Journal of Industry Applications 4, no. 5 (2015): 543–49. http://dx.doi.org/10.1541/ieejjia.4.543.

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Gu, Qin, Jingliang Peng, and Zhigang Deng. "Compression of Human Motion Capture Data Using Motion Pattern Indexing." Computer Graphics Forum 28, no. 1 (2009): 1–12. http://dx.doi.org/10.1111/j.1467-8659.2008.01309.x.

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Wang, Huifang, John B. Weaver, Marvin M. Doyley, Francis E. Kennedy, and Keith D. Paulsen. "Optimized motion estimation for MRE data with reduced motion encodes." Physics in Medicine and Biology 53, no. 8 (2008): 2181–96. http://dx.doi.org/10.1088/0031-9155/53/8/012.

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Yi, P., Q. Zhang, and X. Wei. "Laplacian coordinates-based motion transition for data-driven motion synthesis." IET Image Processing 6, no. 9 (2012): 1331–37. http://dx.doi.org/10.1049/iet-ipr.2012.0186.

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YASUDA, H., R. KAIHARA, S. SAITO, and M. NAKAJIMA. "Motion Belts: Visualization of Human Motion Data on a Timeline." IEICE Transactions on Information and Systems E91-D, no. 4 (2008): 1159–67. http://dx.doi.org/10.1093/ietisy/e91-d.4.1159.

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Kulbacki, Marek, Bartosz Jablonski, Ryszard Klempous, and Jakub Segen. "Learning from Examples and Comparing Models of Human Motion." Journal of Advanced Computational Intelligence and Intelligent Informatics 8, no. 5 (2004): 477–81. http://dx.doi.org/10.20965/jaciii.2004.p0477.

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This paper addresses a problem of creating character animations from motion capture clips. The main problem we want to solve is partition set of primitive motions into appropriate groups according to similarity between motions. We construct motion models to easier extract features of given motions and make animation process more flexible. Using these models we propose measure of discrepancy between motions. Moreover it normalizes length of motions and decreases high dimension of considered motion data, so clustering may take place in dimensionally reduced space. In addition we examine differen

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Fuhrmann, Thomas, and Matthew C. Garthwaite. "Resolving Three-Dimensional Surface Motion with InSAR: Constraints from Multi-Geometry Data Fusion." Remote Sensing 11, no. 3 (2019): 241. http://dx.doi.org/10.3390/rs11030241.

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Interferometric synthetic aperture radar (InSAR) technology has been widely applied to measure Earth surface motions related to natural and anthropogenic crustal deformation phenomena. With the widespread uptake of data captured by the European Space Agency’s Sentinel-1 mission and other recently launched or planned space-borne SAR missions, the usage of the InSAR technique to detect and monitor Earth surface displacements will increase even more in the coming years. However, InSAR can only measure a one-dimensional motion along the radar line of sight (LOS), which makes interpretation and com

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Li, Hai, Selina Khoo, and Hwa Jen Yap. "Differences in Motion Accuracy of Baduanjin between Novice and Senior Students on Inertial Sensor Measurement Systems." Sensors 20, no. 21 (2020): 6258. http://dx.doi.org/10.3390/s20216258.

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This study aimed to evaluate the motion accuracy of novice and senior students in Baduanjin (a traditional Chinese sport) using an inertial sensor measurement system (IMU). Study participants were nine novice students, 11 senior students, and a teacher. The motion data of all participants were measured three times with the IMU. Using the motions of the teacher as the standard motions, we used dynamic time warping to calculate the distances between the motion data of the students and the teacher to evaluate the motion accuracy of the students. The distances between the motion data of the novice

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Brotzer, Andreas, Felix Bernauer, Karl Ulrich Schreiber, Joachim Wassermann, and Heiner Igel. "Automated Quality Assessment of Interferometric Ring Laser Data." Sensors 21, no. 10 (2021): 3425. http://dx.doi.org/10.3390/s21103425.

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In seismology, an increased effort to observe all 12 degrees of freedom of seismic ground motion by complementing translational ground motion observations with measurements of strain and rotational motions could be witnessed in recent decades, aiming at an enhanced probing and understanding of Earth and other planetary bodies. The evolution of optical instrumentation, in particular large-scale ring laser installations, such as G-ring and ROMY (ROtational Motion in seismologY), and their geoscientific application have contributed significantly to the emergence of this scientific field. The curr

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Hoang, Nhat M., Kehong Gong, Chuan Guo, and Michael Bi Mi. "MotionMix: Weakly-Supervised Diffusion for Controllable Motion Generation." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 3 (2024): 2157–65. http://dx.doi.org/10.1609/aaai.v38i3.27988.

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Controllable generation of 3D human motions becomes an important topic as the world embraces digital transformation. Existing works, though making promising progress with the advent of diffusion models, heavily rely on meticulously captured and annotated (e.g., text) high-quality motion corpus, a resource-intensive endeavor in the real world. This motivates our proposed MotionMix, a simple yet effective weakly-supervised diffusion model that leverages both noisy and unannotated motion sequences. Specifically, we separate the denoising objectives of a diffusion model into two stages: obtaining

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Zong, Xing, Chenfei Zhang, and Dengpan Wu. "Research on Data Mining of Sports Wearable Intelligent Devices Based on Big Data Analysis." Discrete Dynamics in Nature and Society 2022 (April 14, 2022): 1–9. http://dx.doi.org/10.1155/2022/3723269.

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Traditional motion data mining models have some problems, such as poor dynamic data capture effect, low information classification effect rate, poor quantitative representation effect, and so on. Based on this, this paper studies the mining method of dynamic motion data based on neural network, constructs a data mining model based on discrete dynamic modeling technology, and realizes the collection of data information from the aspects of motion characteristics and types combined with multilayer sensors. Neural network algorithm is used for comprehensive analysis to realize multivariate analysi

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Chen, Si Xi, Shu Chen, Jian De Lin, Jian Wei Li, and Xin Chen. ""The Seven Claps" of Quan-Zhou Chest-Clapping with Motion Capture." Applied Mechanics and Materials 311 (February 2013): 202–7. http://dx.doi.org/10.4028/www.scientific.net/amm.311.202.

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This paper focuses on the motion capture method of the certain variety of South China traditional folk dance, Quan-zhou Chest-clapping. The authors used Vicon Motion Capture system to capture the motion of “the seven claps”, the basic form of Quan-zhou Chest-clapping Dance, and optimized the capture procedures and acting standards for the clapping and certain motions’ capture. To process the motion data , the authors used the Motionanalysis system to obtain the six degrees of freedom of certain basic dance motions, by measuring the motions’ maximum and minimum values of linear displacements an

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Inayat, Irum, Rooh ul Amin, and Malik Mazhar Ali. "Hardware-in-the-loop flight motion simulation of flexible variable sweep aircraft." Aircraft Engineering and Aerospace Technology 90, no. 9 (2018): 1428–37. http://dx.doi.org/10.1108/aeat-08-2017-0180.

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Purpose This paper aims to propose an improved and computationally efficient motion simulation of a flexible variable sweep aircraft. Design/methodology/approach The motion simulation is performed on hardware-in-the-loop simulation setup using 6 degree-of-freedom motion platform. The dynamic model of a flexible variable sweep aircraft, Rockwell B-1 Lancer is presented using equations of motions for combined rigid and flexible motions. The peak filter is introduced as a new method to separate flexible motion from aircraft motion data. Standard adaptive washout filter is modified and redesigned

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