TY - GEN
T1 - Human action recognition via affine moment invariants
AU - Sadek, Samy
AU - Al-Hamadi, Ayoub
AU - Michaelis, Bernd
AU - Sayed, Usama
PY - 2012
Y1 - 2012
N2 - Despite their high stability and compactness, affine moment invariants have received a relatively little attention in action recognition literature. In this paper, we introduce an approach for activity recognition, based on affine moment invariants. In the proposed approach, a compact computationally-efficient shape descriptor is developed by using affine moment invariants. Affine moment invariants are derived from the 3D spatio-temporal action volume and the average image created from the 3D volume, and classified by an SVM classifier. On KTH dataset, the method achieves performance results that compare favorably with these of other contemporary approaches reported in literature.
AB - Despite their high stability and compactness, affine moment invariants have received a relatively little attention in action recognition literature. In this paper, we introduce an approach for activity recognition, based on affine moment invariants. In the proposed approach, a compact computationally-efficient shape descriptor is developed by using affine moment invariants. Affine moment invariants are derived from the 3D spatio-temporal action volume and the average image created from the 3D volume, and classified by an SVM classifier. On KTH dataset, the method achieves performance results that compare favorably with these of other contemporary approaches reported in literature.
UR - http://www.scopus.com/inward/record.url?scp=84874567204&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84874567204
SN - 9784990644109
T3 - Proceedings - International Conference on Pattern Recognition
SP - 218
EP - 221
BT - ICPR 2012 - 21st International Conference on Pattern Recognition
T2 - 21st International Conference on Pattern Recognition, ICPR 2012
Y2 - 11 November 2012 through 15 November 2012
ER -