Hand Link Modeling and Motion Generation from Motion Capture Data Based on 3D Joint Kinematics

2005 ◽  
Author(s):  
Natsuki Miyata ◽  
Makiko Kouchi ◽  
Masaaki Mochimaru ◽  
Katsuaki Kawachi ◽  
Tsuneya Kurihara
Keyword(s):  
Motion Capture ◽  
Joint Kinematics ◽  
Motion Capture Data ◽  
Motion Generation

scholarly journals An examination of the hamstring and the quadriceps muscle kinematics during the front and back squat in males

2017 ◽  
Vol 9 (1) ◽  
pp. 37-45
Author(s):  
JONATHAN SINCLAIR ◽  
DARRELL BROOKS ◽  
STEPHEN ATKINS
Keyword(s):  
Motion Capture ◽  
Quadriceps Muscle ◽  
Joint Kinematics ◽  
Motion Capture Data ◽  
Current Investigation ◽  
Repetition Maximum ◽  
Paired Samples ◽  
Back Squat ◽  
Hamstring Muscles

The aim of the current investigation was to examine the influence of the front and back squat variants on the hamstring and the quadriceps muscles kinematics. Eighteen male participants were recruited with 1 repetition maximum values of 122.7 ±16.4 and 88.7 ±13.9 kg for the back and front squat lifts. Participants completed both back and front squats at 70% of their front squat 1 repetition maximum. The hamstring and the quadriceps muscle kinematics were determined during kinetic situations using motion capture data, in addition to segmental and joint kinematics. Differences between squat conditions were examined using paired samples t-tests.The results showed that there were no differences in either segmental/joint or muscle kinematics between the front and back squat lifts. These findings lead to the conclusion that neither the front nor the back squat conditions differ in terms of their eccentric and concentric recruitment of the quadriceps and hamstring muscles.

Correlational Methods for Analysis of Dance Movements

2011 ◽  
Vol 29 (supplement) ◽  
pp. 283-304 ◽  
Author(s):  
Timothy R. Brick ◽  
Steven M. Boker
Keyword(s):  
Motion Capture ◽  
Mirror Symmetry ◽  
Cross Correlation ◽  
The Other ◽  
Free Form ◽  
Motion Capture Data ◽  
Complex Interactions ◽  
Dance Movements ◽  
Time Lagged ◽  
Insight Into

Among the qualities that distinguish dance from other types of human behavior and interaction are the creation and breaking of synchrony and symmetry. The combination of symmetry and synchrony can provide complex interactions. For example, two dancers might make very different movements, slowing each time the other sped up: a mirror symmetry of velocity. Examining patterns of synchrony and symmetry can provide insight into both the artistic nature of the dance, and the nature of the perceptions and responses of the dancers. However, such complex symmetries are often difficult to quantify. This paper presents three methods – Generalized Local Linear Approximation, Time-lagged Autocorrelation, and Windowed Cross-correlation – for the exploration of symmetry and synchrony in motion-capture data as is it applied to dance and illustrate these with examples from a study of free-form dance. Combined, these techniques provide powerful tools for the examination of the structure of symmetry and synchrony in dance.

Perceptually motivated LSPIHT for motion capture data compression

2015 ◽  
Vol 51 ◽  
pp. 1-7 ◽  
Author(s):  
Irene Cheng ◽  
Amirhossein Firouzmanesh ◽  
Anup Basu
Keyword(s):  
Data Compression ◽  
Motion Capture ◽  
Motion Capture Data

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
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