论文标题
观察不变的动作识别
View-invariant action recognition
论文作者
论文摘要
人类行动识别是计算机视觉中的重要问题。它在监视，人为计算机互动，增强现实，视频索引和检索方面具有广泛的应用。人类作用产生的时空外观的不同模式是识别执行动作的关键。我们已经看到了许多研究，探索了这种时空外观的动态，以学习人类行为的视觉表现。但是，大多数行动识别的研究都集中在某些共同的观点上，并且当观点发生变化时，这些方法的表现不佳。人类的行动是在三维环境中进行的，当从给定的角度捕获为视频时，被预测到二维空间。因此，从不同角度来看，动作将具有不同的时空外观。观察不变的行动识别中的研究解决了这个问题，并着重于从看不见的观点识别人类行为。
Human action recognition is an important problem in computer vision. It has a wide range of applications in surveillance, human-computer interaction, augmented reality, video indexing, and retrieval. The varying pattern of spatio-temporal appearance generated by human action is key for identifying the performed action. We have seen a lot of research exploring this dynamics of spatio-temporal appearance for learning a visual representation of human actions. However, most of the research in action recognition is focused on some common viewpoints, and these approaches do not perform well when there is a change in viewpoint. Human actions are performed in a 3-dimensional environment and are projected to a 2-dimensional space when captured as a video from a given viewpoint. Therefore, an action will have a different spatio-temporal appearance from different viewpoints. The research in view-invariant action recognition addresses this problem and focuses on recognizing human actions from unseen viewpoints.
