We use concepts from chaos theory in order to model
nonlinear dynamical systems that exhibit deterministic behavior.
Observed time series from such a system can be embedded
into...
The recognition of activities from sensory data is important in advanced surveillance systems to enable prediction of high-level goals and intentions of the target under surveilla...
Nam Thanh Nguyen, Hung Hai Bui, Svetha Venkatesh, ...
A representative subspace is significant for image analysis, while the corresponding techniques often suffer from the curse of dimensionality dilemma. In this paper, we propose a ...
Dong Xu, Shuicheng Yan, Lei Zhang, HongJiang Zhang...
While crowds of various subjects may offer applicationspecific cues to detect individuals, we demonstrate that for the general case, motion itself contains more information than p...
We propose a novel unsupervised learning framework for activity perception. To understand activities in complicated scenes from visual data, we propose a hierarchical Bayesian mod...