We propose a principled framework to model persistent motion in dynamic scenes. In contrast to previous efforts on object tracking and optical flow estimation that focus on local...
—One way of modelling the wireless channel is in a statistical manner, based on a few parameters describing the characteristics of the environment. In most current wireless chann...
We introduce in this paper a generalization of the widely used hidden Markov models (HMM's), which we name "structural hidden Markov models" (SHMM). Our approach is ...
Extremely crowded scenes present unique challenges to
video analysis that cannot be addressed with conventional
approaches. We present a novel statistical framework for
modeling...
Louis Kratz (Drexel University), Ko Nishino (Drexe...
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...