scholarly journals Human Motion Capture Based on Incremental Dimension Reduction and Projection Position Optimization

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Wanyi Li ◽  
Yuqi Zeng ◽  
Qian Zhang ◽  
Yilin Wu ◽  
Guoming Chen
Keyword(s):  
Dimension Reduction ◽  
Motion Capture ◽  
Three Dimensional ◽  
Human Motion ◽  
The Other ◽  
High Dimensional ◽  
Key Technology ◽  
Human Motion Capture ◽  
Low Dimensional ◽  
Multimedia Product

Three-dimensional (3D) human motion capture is a hot researching topic at present. The network becomes advanced nowadays, the appearance of 3D human motion is indispensable in the multimedia works, such as image, video, and game. 3D human motion plays an important role in the publication and expression of all kinds of medium. How to capture the 3D human motion is the key technology of multimedia product. Therefore, a new algorithm called incremental dimension reduction and projection position optimization (IDRPPO) is proposed in this paper. This algorithm can help to learn sparse 3D human motion samples and generate the new ones. Thus, it can provide the technique for making 3D character animation. By taking advantage of the Gaussian incremental dimension reduction model (GIDRM) and projection position optimization, the proposed algorithm can learn the existing samples and establish the relevant mapping between the low dimensional (LD) data and the high dimensional (HD) data. Finally, the missing frames of input 3D human motion and the other type of 3D human motion can be generated by the IDRPPO.

Design of Multi-User Aerobics Wireless Human Motion Capture System Based on MEMS

2013 ◽  
Vol 650 ◽  
pp. 518-522
Author(s):  
Juan Xiao
Keyword(s):  
Real Time ◽  
Motion Capture ◽  
Large Scale ◽  
Three Dimensional ◽  
Human Motion ◽  
Motion Capture System ◽  
Human Motion Capture ◽  
Large Scale Data ◽  
Core Technology ◽  
Real Time Transmission

Main characteristics of recent human motion capture systems are analyzed in the paper firstly. Based on that, a new multi-user aerobics wireless human motion capture system based on MEMS is proposed. Design of its framework and core technology solutions including large-scale data obtain, multi-hop wireless sensor and high-frequency real-time transmission are put forward. Finally, three-dimensional real-time reconstructions of the multi-user aerobics wireless motion capture system are showed in the paper.

scholarly journals Optical motion capture dataset of selected techniques in beginner and advanced Kyokushin karate athletes

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Agnieszka Szczęsna ◽  
Monika Błaszczyszyn ◽  
Magdalena Pawlyta
Keyword(s):  
Motion Capture ◽  
Three Dimensional ◽  
Data File ◽  
Human Motion ◽  
Skill Levels ◽  
Human Motion Capture ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Capture Techniques ◽  
Karate Athletes

AbstractHuman motion capture is commonly used in various fields, including sport, to analyze, understand, and synthesize kinematic and kinetic data. Specialized computer vision and marker-based optical motion capture techniques constitute the gold-standard for accurate and robust human motion capture. The dataset presented consists of recordings of 37 Kyokushin karate athletes of different ages (children, young people, and adults) and skill levels (from 4th dan to 9th kyu) executing the following techniques: reverse lunge punch (Gyaku-Zuki), front kick (Mae-Geri), roundhouse kick (Mawashi-Geri), and spinning back kick (Ushiro-Mawashi-Geri). Each technique was performed approximately three times per recording (i.e., to create a single data file), and under three conditions where participants kicked or punched (i) in the air, (ii) a training shield, or (iii) an opponent. Each participant undertook a minimum of two trials per condition. The data presented was captured using a Vicon optical motion capture system with Plug-In Gait software. Three dimensional trajectories of 39 reflective markers were recorded. The resultant dataset contains a total of 1,411 recordings, with 3,229 single kicks and punches. The recordings are available in C3D file format. The dataset provides the opportunity for kinematic analysis of different combat sport techniques in attacking and defensive situations.

scholarly journals On the Kirchhoff-Love Hypothesis (Revised and Vindicated)

2021 ◽  
Author(s):  
Olivier Ozenda ◽  
Epifanio G. Virga
Keyword(s):  
Free Energy ◽  
Dimension Reduction ◽  
Three Dimensional ◽  
Energy Functional ◽  
The Other ◽  
Variational Model ◽  
Two Dimensional ◽  
Elastic Plates ◽  
Kinematic Constraint ◽  
Free Energy Functional

AbstractThe Kirchhoff-Love hypothesis expresses a kinematic constraint that is assumed to be valid for the deformations of a three-dimensional body when one of its dimensions is much smaller than the other two, as is the case for plates. This hypothesis has a long history checkered with the vicissitudes of life: even its paternity has been questioned, and recent rigorous dimension-reduction tools (based on standard $\varGamma $ Γ -convergence) have proven to be incompatible with it. We find that an appropriately revised version of the Kirchhoff-Love hypothesis is a valuable means to derive a two-dimensional variational model for elastic plates from a three-dimensional nonlinear free-energy functional. The bending energies thus obtained for a number of materials also show to contain measures of stretching of the plate’s mid surface (alongside the expected measures of bending). The incompatibility with standard $\varGamma $ Γ -convergence also appears to be removed in the cases where contact with that method and ours can be made.

Keyframe Extraction for Human Motion Capture Data Based on Joint Kernel Sparse Representation

2017 ◽  
Vol 64 (2) ◽  
pp. 1589-1599 ◽  
Author(s):  
Guiyu Xia ◽  
Huaijiang Sun ◽  
Xiaoqing Niu ◽  
Guoqing Zhang ◽  
Lei Feng
Keyword(s):  
Sparse Representation ◽  
Motion Capture ◽  
Human Motion ◽  
Motion Capture Data ◽  
Human Motion Capture ◽  
Keyframe Extraction

Sensor network oriented human motion capture via wearable intelligent system

2021 ◽  
Author(s):  
Sen Qiu ◽  
Hongkai Zhao ◽  
Nan Jiang ◽  
Donghui Wu ◽  
Guangcai Song ◽  
...  
Keyword(s):  
Sensor Network ◽  
Motion Capture ◽  
Intelligent System ◽  
Human Motion ◽  
Human Motion Capture

A Low-Dimensional Dissimilarity Analysis of Unilateral and Bilateral Stroke-Impacted Hand Trajectories

2016 ◽  
Vol 138 (11) ◽  
Author(s):  
Jay Ryan U. Roldan ◽  
Dejan Milutinović ◽  
Zhi Li ◽  
Jacob Rosen
Keyword(s):  
Multidimensional Scaling ◽  
Healthy Subject ◽  
Motion Capture ◽  
Early Phase ◽  
Three Dimensional ◽  
High Rate ◽  
Motion Capture System ◽  
Trajectory Data ◽  
The Difference ◽  
Low Dimensional

In this paper, we propose a quantitative approach based on identifying hand trajectory dissimilarities through the use of a multidimensional scaling (MDS) analysis. A high-rate motion capture system is used to gather three-dimensional (3D) trajectory data of healthy and stroke-impacted hemiparetic subjects. The mutual dissimilarity between any two trajectories is measured by the area between them. This area is used as a dissimilarity variable to create an MDS map. The map reveals a structure for measuring the difference and variability of individual trajectories and their groups. The results suggest that the recovery of hemiparetic subjects can be quantified by comparing the difference and variability of their individual MDS map points to the points from the cluster of healthy subject trajectories. Within the MDS map, we can identify fully recovered patients, those who are only functionally recovered, and those who are either in an early phase of, or are nonresponsive to the therapy.

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