TY - GEN
T1 - Human action recognition by Radon transform
AU - Chen, Yan
AU - Wu, Qiang
AU - He, Xiangjian
PY - 2008
Y1 - 2008
N2 - A new feature description is used for human behaviour representation and recognition. The feature is based on Radon transforms of extracted silhouettes. Key postures are selected based on the Radon transform. Key postures are combined to construct an action template for each sequence. Linear Discriminant Analysis (LDA) is applied to the set of key postures to obtain low dimensional feature vectors. Different classification methods are used to classify each sequence. Experiments are carried out based on a publically available human behaviour database and the results are exciting.
AB - A new feature description is used for human behaviour representation and recognition. The feature is based on Radon transforms of extracted silhouettes. Key postures are selected based on the Radon transform. Key postures are combined to construct an action template for each sequence. Linear Discriminant Analysis (LDA) is applied to the set of key postures to obtain low dimensional feature vectors. Different classification methods are used to classify each sequence. Experiments are carried out based on a publically available human behaviour database and the results are exciting.
UR - http://www.scopus.com/inward/record.url?scp=62449107760&partnerID=8YFLogxK
U2 - 10.1109/ICDMW.2008.26
DO - 10.1109/ICDMW.2008.26
M3 - Conference contribution
AN - SCOPUS:62449107760
SN - 9780769535036
T3 - Proceedings - IEEE International Conference on Data Mining Workshops, ICDM Workshops 2008
SP - 862
EP - 868
BT - Proceedings - IEEE International Conference on Data Mining Workshops, ICDM Workshops 2008
T2 - IEEE International Conference on Data Mining Workshops, ICDM Workshops 2008
Y2 - 15 December 2008 through 19 December 2008
ER -