論文翻譯：A New Representation of Skeleton Sequences for 3D Action Recognition
提出了一種利用骨骼序列進行三維動作識別的新方法。，人體骨骼關節的三維軌跡)。該方法首先將每個骨架序列轉換爲三個片段，每個片段由若干幀組成，然後利用深度神經網絡進行時空特徵學習。每個剪輯由骨架序列的柱座標的一個通道生成。所生成的片段的每一幀代表了整個骨架序列的時間信息。並結合了關節之間的特定空間關係。整個剪輯包含多個具有不同空間關係的幀，爲人體骨骼提供了有用的空間結構信息。我們建議使用深卷積神經網絡
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- 1. [骨架動作識別]A New Representation of Skeleton Sequences for 3D Action Recognition
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相關文章
- 1. [骨架動作識別]A New Representation of Skeleton Sequences for 3D Action Recognition
- 2. 論文翻譯：Unsupervised Representation Learning with Long-Term Dynamics for Skeleton Based Action Recognit
- 3. 論文翻譯：Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
- 4. 論文翻譯：Deep Progressive Reinforcement Learning for Skeleton-based Action Recognition
- 5. 【論文翻譯】An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition
- 6. Representation Flow for Action Recognition論文解讀
- 7. 論文翻譯：Skeleton Based Human Action Recognition with Global Context-Aware Attention LSTM Networks
- 8. 論文：3D Convolutional Neural Networks for Human Action Recognition
- 9. Representation Flow for Action Recognition
- 10. 論文翻譯：Make Skeleton-based Action Recognition Model Smaller, Faster and Better