A point cloud similarity approach to find repetitive patterns in continuous 3D human motion data.
Description
Repetitive patterns are segments that appear frequently in a given signal. The signal data can be either discrete or continuous. For a discrete signal, repetitive patterns can be found by exact matching with string matching techniques or inexact matching with dynamic programming. Unlike discrete signals, a continuous signal contains an infinite number of states, so it is impractical to identify exactly matched states. Hence, a point cloud similarity approach is proposed to inexactly match similar segment pairs and then approximate the optimal matching.
Team Members
- Jeff, Kai-Tai Tang — itjeff@cityu.edu.hk
- Howard Leung — howard@cityu.edu.hk
- Taku Komura
- Hubert Pak-Ho Shum