In this paper, we present a view-independent action recognition method exploiting a low computational-cost volumetric action representation. Binary images depicting the human body during action execution are accumulated in order to produce the so-called action volumes. A novel time-invariant action representation is obtained by exploiting the circular shift invariance property of the magnitudes...

A long standing debate revolves around the question whether visual action recognition primarily relies on visual or motor action information. Previous studies mainly examined the contribution of either visual or motor information to action recognition. Yet, the interaction of visual and motor action information is particularly important for understanding action recognition in social interaction...

Human action recognition has been an active research area in recent years. However, building a robust human action recognition system still remains a challenging task due to the large variations in action classes, varying human appearances, illumination changes, camera motion, occlusions and background clutter. Most previous work focus on the goal of improving recognition rates. This paper desc...

This report addresses the problem of using probabilistic formal languages to describe and understand actions with explicit structure. The paper explores a probabilistic mechanisms of parsing the uncertain input string aided by a stochastic context-free grammar. This method, originating in speech recognition, allows for combination of a statistical recognition approach with a syntactical one in ...

This paper concentrates on the comparisons of systems that are used for the recognition of expressions generated by six upper face action units (AU s) by using Facial Action Coding System (FACS). Haar wavelet, Haar-Like and Gabor wavelet coe cients are compared, using Adaboost for feature selection. The binary classi cation results by using Support Vector Machines (SVM ) for the upper face AU s...

Recently still image-based human action recognition has become an active research topic in computer vision and pattern recognition. It focuses on identifying a person's action or behavior from a single image. Unlike the traditional action recognition approaches where videos or image sequences are used, a still image contains no temporal information for action characterization. Thus the prevaili...