Abstract
A framework for human action modeling and recognition in continuous action sequences is proposed. A star figure enclosed by a bounding convex polygon is used to effectively represent the extremities of the silhouette of a human body. Thus, human actions are recorded as a sequence of the star figure's parameters, which is then used for action modeling. To model human actions in a compact manner while characterizing their spatio-temporal patterns, star figure parameters are represented by a 2-D feature map, which is used and regarded as a spatio-temporal template. Experiments to evaluate the performance of the proposed framework show that it can recognize human actions in an efficient and effective manner.