Reordering-based transform for compressing human motion capture data

Junhui Hou, Lap-Pui Chau, Ying He, Nadia Magnenat-Thalmann

Abstract: This paper presents a simple yet effective algorithm for compressing human motion capture (mocap) data. With a reordering-based discrete wavelet transform and the standard discrete cosine transform, our method can effectively reduce the spatial and temporal correlation in mocap data. Our method is conceptually simple and easy to implement. Experimental results show that our method can achieve better compression performance with lower latency, compared to the state-of-the-art methods.