Action Recognition for Depth Video using Multi-view Dynamic Images

Understand

Dynamic imaging is a recently proposed action description paradigm for simultaneously capturing motion and temporal evolution information, particularly in the context of deep convolutional neural networks (CNNs).

• Compared with optical flow for motion characterization, dynamic imaging exhibits superior efficiency and compactness.
• Inspired by the success of dynamic imaging in RGB video, this study extends it to the depth domain.
• To better exploit three-dimensional (3D) characteristics, multi-view dynamic images are proposed.