@conference {13071, title = {Action recognition using Partial Least Squares and Support Vector Machines}, booktitle = {Image Processing (ICIP), 2011 18th IEEE International Conference on}, year = {2011}, month = {2011/09//}, pages = {533 - 536}, abstract = {We introduce an action recognition approach based on Partial Least Squares (PLS) and Support Vector Machines (SVM). We extract very high dimensional feature vectors representing spatio-temporal properties of actions and use multiple PLS regressors to find relevant features that distinguish amongst action classes. Finally, we use a multi-class SVM to learn and classify those relevant features. We applied our approach to INRIA{\textquoteright}s IXMAS dataset. Experimental results show that our method is superior to other methods applied to the IXMAS dataset.}, keywords = {analysis;support, approach;multiclass, approximations;regression, dataset;action, dimensional, extraction;feature, extraction;image, feature, high, INRIA, IXMAS, least, machines;, machines;very, partial, properties;support, recognition, recognition;least, regressors;spatiotemporal, squares, SVM;multiple, vector, vectors}, doi = {10.1109/ICIP.2011.6116399}, author = {Ramadan,S. and Davis, Larry S.} }