Motion data compression using sparse representation
稀疏表达的运动数据压缩

As motion capture data is widely used nowadays, the compression of motion data becomes more and more important. In this paper, a sparse representation based approach is proposed for efficient compression of human motion data. A new algorithm is designed to extract the dictionary from an input motion clip automatically. Each frame of a motion clip can be represented by a sparse linear combination of the dictionary vectors. The experimental results show that our method can get a high compression ratio (about 50 times) for general short motion data, with a limited reconstruction error, which is hard to visually distinguish (ARMS error less than 2.0).