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Research on three-dimensional modeling and motion capture technology for accordion playing hand posture

 oraz   
17 mar 2025

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Figure 1.

Three-dimensional skeleton and leather weight of template network model
Three-dimensional skeleton and leather weight of template network model

Figure 2.

Comparison of error distribution on sequence 1st
Comparison of error distribution on sequence 1st

Figure 3.

Comparison of error distribution on a case with occlusion
Comparison of error distribution on a case with occlusion

Figure 4.

Comparison of per-frame mean numerical errors on sequence 1
Comparison of per-frame mean numerical errors on sequence 1

Figure 5.

Schematic of the motion structure of the hand joint
Schematic of the motion structure of the hand joint

Figure 6.

Hand gesture recognition performance under dependence
Hand gesture recognition performance under dependence

Figure 7.

Hand gesture recognition performance under user independence
Hand gesture recognition performance under user independence

Statistics of two test sequences in the experiments

Sequence Frame number Anchor point Vertex number Occlusion Capture device
1 450 13 40~68k Yes IVCam
2 450 16 8~12k Yes Kinect

Delay of each model

Models Delay/ms
SVM 114
K-close 138
FNN 153
Boosting 109

Accuracy of each hand gesture recognition

Hand gesture A/%
Natural relaxation 98.32
Basic position 98.27
Finger independence 96.49
Finger curvature 96.54
Span 98.83
Weight and speed 98.47
Wrist position 98.09
Shoulder position 98.52
Arm position 98.13
Język:
Angielski
Częstotliwość wydawania:
1 razy w roku
Dziedziny czasopisma:
Nauki biologiczne, Nauki biologiczne, inne, Matematyka, Matematyka stosowana, Matematyka ogólna, Fizyka, Fizyka, inne