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 ...
In this paper, we show that in a multi-camera context, we can effectively handle occlusions in real-time at each frame independently, even when the only available data comes from ...
In this work, we propose a new super-resolution algorithm to simultaneously estimate all frames of a video sequence. The new algorithm is based on the Bayesian maximum a posterior...
We propose the use of 3D (2D+time) Shape Context to recognize the spatial and temporal details inherent in human actions. We represent an action in a video sequence by a 3D point ...
Franziska Meier, Irfan A. Essa, Matthias Grundmann
Despite leaps in motion capture technology, the dichotomy between unencumbered vision-based motion recovery and the prevailing marker-assisted motion capture solution remains larg...