We explore an approach to 3D people tracking with learned motion models and deterministic optimization. The tracking problem is formulated as the minimization of a differentiable ...
In this paper, we present a Bayesian framework for the fully automatic tracking of a variable number of interacting targets using a fixed camera. This framework uses a joint multi...
Kevin Smith, Daniel Gatica-Perez, Jean-Marc Odobez
We consider probabilistic methods to compute the near midair collision risk using state estimate and covariance from a target tracking filter based on angle-only sensors such as ...
Even if the problem of human action categorization from videos has received a lot of attention during the past decade, it remains a challenging problem in operative conditions due...
Using eye tracking, we study the way viewers look at photos and image based NPR illustrations. Viewers examine the same number of locations in photos and in NPR images with unifor...