TY - GEN
T1 - Human action recognition based on two-view optical flow in the transformed domain
AU - Abdelwahab, Mohamed A.
AU - Abdelwahab, Moataz M.
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/9/23
Y1 - 2014/9/23
N2 - In this paper a human action recognition algorithm based on two-view of optical flow in multiple layers per camera employing the transform domain and 2DPCA is presented. This method explores more distinctive features between actions. It is not sensitive to translation, alignment and noise. In addition the use of 2DPCA maintains the spatial relation between pixels and increases the recognition accuracy. Experimental results performed on the Weizmann and IXMAS datasets confirm these excellent properties compared to recent reported methods.
AB - In this paper a human action recognition algorithm based on two-view of optical flow in multiple layers per camera employing the transform domain and 2DPCA is presented. This method explores more distinctive features between actions. It is not sensitive to translation, alignment and noise. In addition the use of 2DPCA maintains the spatial relation between pixels and increases the recognition accuracy. Experimental results performed on the Weizmann and IXMAS datasets confirm these excellent properties compared to recent reported methods.
UR - http://www.scopus.com/inward/record.url?scp=84908472677&partnerID=8YFLogxK
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U2 - 10.1109/MWSCAS.2014.6908537
DO - 10.1109/MWSCAS.2014.6908537
M3 - Conference contribution
AN - SCOPUS:84908472677
T3 - Midwest Symposium on Circuits and Systems
SP - 805
EP - 808
BT - 2014 IEEE 57th International Midwest Symposium on Circuits and Systems, MWSCAS 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE 57th International Midwest Symposium on Circuits and Systems, MWSCAS 2014
Y2 - 3 August 2014 through 6 August 2014
ER -