In this paper, we address the problem of representing human actions using visual cues for the purpose of learning and recognition. Traditional approaches model actions as space-ti...
Abstract-- This paper presents a novel framework for integrating fundamental tasks in robotic navigation through a statistical inference procedure. A probabilistic model that joint...
We address recognition and localization of human actions in realistic scenarios. In contrast to the previous work studying human actions in controlled settings, here we train and ...
The time varying human multijoint arm dynamics can be modeled by two factors, simplified musculoskeletal dynamics and the uncertainty factor consisting of measurement noises and m...
Humans are articulated objects composed of non-rigid parts. We are interested in detecting and tracking human motions over various periods of time. In this paper we describe a met...