TY - JFULL AU - S. Maheswari and P. Arockia Jansi Rani PY - 2015/12/ TI - Human Action Recognition System Based on Silhouette T2 - International Journal of Computer and Information Engineering SP - 2389 EP - 2394 VL - 9 SN - 1307-6892 UR - https://publications.waset.org/pdf/10004913 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 107, 2015 N2 - Human action is recognized directly from the video sequences. The objective of this work is to recognize various human actions like run, jump, walk etc. Human action recognition requires some prior knowledge about actions namely, the motion estimation, foreground and background estimation. Region of interest (ROI) is extracted to identify the human in the frame. Then, optical flow technique is used to extract the motion vectors. Using the extracted features similarity measure based classification is done to recognize the action. From experimentations upon the Weizmann database, it is found that the proposed method offers a high accuracy. ER -