In this paper, we propose a method for recovering the reflectance properties of a moving Lambertian object from an image sequence of the object taken by a fixed camera under unkno...
Akihiro Sugimoto, Fei Du, Takahiro Okabe, Yoichi S...
We propose a generative statistical approach to human motion modeling and tracking that utilizes probabilistic latent semantic (PLSA) models to describe the mapping of image featu...
The complexity of dynamical laws governing 3D atmospheric flows associated to incomplete and noisy observations makes very difficult the recovery of atmospheric dynamics from sate...
A method for detecting and segmenting periodic motion is presented. We exploit periodicity as a cue and detect periodic motion in complex scenes where common methods for motion se...
We propose a new model for the probabilistic estimation of continuous state variables from a sequence of observations, such as tracking the position of an object in video. This ma...