Accuracy (Body + Fingers joints): 91.78Accuracy (Body joints): 89.56Accuracy (Body + Fingers + Face joints): 89.64
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Skeleton Based Action Recognition
Skeleton-based Action Recognition is a computer vision task that involves recognizing human actions from a sequence of 3D skeletal joint data captured from sensors such as Microsoft Kinect, Intel RealSense, and wearable devices. The goal of skeleton-based action recognition is to develop algorithms that can understand and classify human actions from skeleton data, which can be used in various applications such as human-computer interaction, sports analysis, and surveillance.
<span style="color:grey; opacity: 0.6">( Image credit: View Adaptive Neural Networks for High Performance Skeleton-based Human Action Recognition )</span>
논문
Accuracy: 98.02%
Accuracy (Cross-Subject): 57.01 %
Accuracy: 97.45
Accuracy: 96.00%
Accuracy: 95.7%
Accuracy: 91.7%
1:3 Accuracy: 92.91:1 Accuracy: 95.933:1 Accuracy: 96.76Cross-person Accuracy: 88.70
1:1 Accuracy: 96.17
PCK@0.1: 45.2PCK@0.2: 62.9PCK@0.3: 73.5PCK@0.4: 80.6
Accuracy: 96.00%
Accuracy: 90.9%
1:1 Accuracy: 94.43
Accuracy: 98.60%
PCK@0.1: 58.4PCK@0.2: 78.1PCK@0.3: 85.9PCK@0.4: 89.8
Accuracy: 99.02%
Accuracy: 98.4%
Accuracy: 93.96
Accuracy: 91.40%
Accuracy: 94.0%
Accuracy: 99.1%
Accuracy: 93.3%
PCK@0.1: 45.2PCK@0.2: 69.6PCK@0.3: 80.8PCK@0.4: 87.5
Accuracy: 98.3%