Viewpoint insensitive action recognition using envelop shape

Action recognition is a popular and important research topic in computer vision. However, it is challenging when facing viewpoint variance. So far, most researches in action recognition remain rooted in view-dependent representations. Some view invariance approaches have been proposed, but most of them suffer from some weaknesses, such as lack of abundant information for recognition, dependency on robust meaningful feature detection or point correspondence. To perform viewpoint and subject independent action recognition, we propose a representation named '' Envelop Shape '' which is viewpoint insensitive. '' Envelop Shape '' is easy to acquire from silhouettes using two orthogonal cameras. It makes full use of two cameras' silhouettes to dispel influence caused by human body's vertical rotation, which is often the primary viewpoint variance. With the help of '' Envelop Shape '', we obtained inspiring results on action recognition independent of subject and viewpoint. Results indicate that '' Envelop Shape '' representation contains enough discriminating features for action recognition.