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
The paper describes a simple but effective framework for visual object tracking in video sequences. The main contribution of this work lies in the introduction of a case-based rea...
We present algorithms for automatic feature selection for unsupervised structure discovery from video sequences. Feature selection in this scenario is hard because of the absence ...
In this paper, we tackle the problem of object detection and tracking in a new and challenging domain of wide area surveillance. This problem poses several challenges: large camera...
In this paper, we present a Deformable Action Template
(DAT) model that is learnable from cluttered real-world
videos with weak supervisions. In our generative model,
an action ...