A New Representation of Skeleton Sequences for 3D Action Recognition

Understand

This paper presents a new method for 3D action recognition with skeleton sequences (i.e., 3D trajectories of human skeleton joints).

• The proposed method first transforms each skeleton sequence into three clips each consisting of several frames for spatial temporal feature learning using deep neural networks.
• Each clip is generated from one channel of the cylindrical coordinates of the skeleton sequence.
• Each frame of the generated clips represents the temporal information of the entire skeleton sequence, and incorporates one particular spatial relationship between the joints.