This paper presents a graphical model for learning and recognizing human actions.
Specifically, we propose to encode actions in a weighted directed graph, referred to as …

Human action analysis based on 3D imaging is an emerging topic. This paper presents an
approach for the problem of action recognition using information from a number of action …

In this study, a method for human action recognition is proposed. Only one camera is used,
without calibration. Viewpoint invariance is obtained by several acquisitions of the same …

Understanding and defining the meaning of “action” is substantial for robotics research. This
becomes utterly evident when aiming at equip** autonomous robots with robust …

The analysis of moving objects in image sequences (video) has been one of the major
themes in computer vision. In this paper, we focus on video-surveillance tasks; more …

In this study a new approach is presented for the recognition of human actions of everyday
life with a fixed camera. The originality of the presented method consists in characterizing …

An accurate representation of occupancy schedules is needed to assess potential energy
savings from occupancy-based controls in residential buildings. In this study the variation in …

Many approaches to trajectory analysis, such as clustering or classification, use probabilistic
generative models, thus not requiring trajectory alignment/registration. Switched linear …

Automatic trajectory classification has countless applications, ranging from the natural
sciences, such as zoology and meteorology, to urban planning, sports analysis, and …

We introduce a new mono-camera system with multi-infrared lights for human posture
recognition, which is based on the 3D body shape recovered from the body silhouette and …