Most work in human activity recognition is limited to relatively simple behaviors like sitting down, standing up or other dramatic posture changes. Very little has been achieved i...
This paper presents a methodology for automatically identifying human actions in either the frontal or the lateral view. By tracking the movement of the head of the subject over s...
In this paper we demonstrate a fully automated approach for discovering and monitoring patterns of daily activities. Discovering patterns of daily activities and tracking them can...
This paper shows how the output of a number of detection and tracking algorithms can be fused to achieve robust tracking of people in an indoor environment. The new tracking system...
In this paper, we introduce a first-order probabilistic model that combines multiple cues to classify human activities from video data accurately and robustly. Our system works in...