Human action recognition using spatio-temoporal descriptor

A novel and efficient human action recognition method utilizing spatio-temporal interest point detector and 3D speed up robust features (3D SURF) descriptor is proposed. The spatio-temporal interest points are detected using two separate linear filters. Then 3D SURF descriptor is presented and demonstrated in detail to represent the local region around interest point. The experimental results on KTH and Weizmann dataset prove that the proposed method is superior to similar methods. Especially, compared with the popular 3DSIFT, 3D SURF is advantage in recognition rate and lower computation cost as well.