譯：Action Recognition with Improved Trajectories
改進軌跡的行動識別 摘要：最近，密集軌跡被證實是用於動做識別的有效視頻表示，而且在各類數據集上實現了最早進的結果。本論文經過考慮相機的運動來糾正它們，從而改善了它們的性能。爲了估計相機運動，咱們使用SURF描述符和密集光流來匹配幀之間的特徵點，這些特徵點被證實是互補的。而後，這些匹配用於使用RANSAC穩健地估計單應性。人體運動一般與相機運動不一樣，併產生不一致的匹配。爲了改進估計，使用人類檢測器
相關文章
- 1. 譯：Action Recognition with Improved Trajectories
- 2. Action Recognition:iDT論文解讀(Improved Dense Trajectories)
- 3. 譯：Two-stream convolutional networks for action recognition in videos
- 4. 行爲識別筆記：improved dense trajectories算法（iDT算法）
- 5. 行人屬性「Contextual Action Recognition with R*CNN」
- 6. 論文翻譯：Skeleton-Based Action Recognition with Directed Graph Neural Networks
- 7. 論文翻譯：Skeleton-Based Action Recognition with Multi-Stream Adaptive Graph Convolutional Networks
- 8. 論文翻譯：Skeleton Based Human Action Recognition with Global Context-Aware Attention LSTM Networks
- 9. Spatiotemporal Residual Networks for Video Action Recognition
- 10. 【視頻行爲識別0】傳統方法：Dense Trajectories(DT)和Improved Dense Trajectories(IDT)算法（ICCV2013）
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相關文章
- 1. 譯：Action Recognition with Improved Trajectories
- 2. Action Recognition:iDT論文解讀(Improved Dense Trajectories)
- 3. 譯：Two-stream convolutional networks for action recognition in videos
- 4. 行爲識別筆記：improved dense trajectories算法（iDT算法）
- 5. 行人屬性「Contextual Action Recognition with R*CNN」
- 6. 論文翻譯：Skeleton-Based Action Recognition with Directed Graph Neural Networks
- 7. 論文翻譯：Skeleton-Based Action Recognition with Multi-Stream Adaptive Graph Convolutional Networks
- 8. 論文翻譯：Skeleton Based Human Action Recognition with Global Context-Aware Attention LSTM Networks
- 9. Spatiotemporal Residual Networks for Video Action Recognition
- 10. 【視頻行爲識別0】傳統方法：Dense Trajectories(DT)和Improved Dense Trajectories(IDT)算法（ICCV2013）