A Dimension Reduction Method Using LSDA For Human Action Recognition

摘要

Since dimensionality disaster easily occurs in the processing of dealing with video data, a dimensionality reduction method, linear sequence discriminate analysis (LSDA), is proposed for human action recognition. The experimental results conducted on KTH datasets and UCF101 datasets show that the proposed method has improved the recognition accuracy.