Title :
Human action recognition using 3D zernike moments
Author :
Arik, Okay ; Semih Bingol, A.
Author_Institution :
Dept. of Electr. & Electron. Eng., Hacettepe Univ., Ankara, Turkey
Abstract :
In this work, 3D Zernike moments have been used to classify 7 basic coarse human actions in markerless 3D video sequences. The time trajectories of the Zernike moments of the moving subject have been taken as features. Even though Zernike moment orders of about 15 to 20 are required to characterize and/or reconstruct a general 3D image with reasonable fidelity, it has been found that fewer number of moments are sufficient for satisfactory action classification, due to the accumulative nature of video data. In our work, we have obtained greater than 95% recognition accuracy using as low as 3rd order Zernike moments, over the 7 basic actions considered. Recognition accuracy increased to more than 98% with 5th order moments.
Keywords :
image classification; image motion analysis; image reconstruction; image sequences; object recognition; video signal processing; 3D Zernike moments; general 3D image characterization; general 3D image reconstruction; human action classification; human action recognition; markerless 3D video sequences; Accuracy; Character recognition; Image recognition; Zinc; Action Recognition; Pose estimation; Zernike Moments;
Conference_Titel :
Multi-Conference on Systems, Signals & Devices (SSD), 2014 11th International
Conference_Location :
Barcelona
DOI :
10.1109/SSD.2014.6808758