A framework for learning parameterized models of optical flow from image sequences is presented. A class of motions is represented by a set of orthogonal basis flow fields that ar...
Michael J. Black, Yaser Yacoob, Allan D. Jepson, D...
We introduce in this paper two probabilistic reasoning models (PRM-1 and PRM-2) which combine the Principal Component Analysis (PCA) technique and the Bayes classifier and show th...
This paper advocates an implicit-surface representation of generic 3?D surfaces to take advantage of occluding edges in a very robust way. This lets us exploit silhouette constrai...
In an extended image sequence of an outdoor scene, one observes changes in color induced by variations in the spectral composition of daylight. This paper proposes a model for the...
Kalyan Sunkavalli, Fabiano Romeiro, Wojciech Matus...
Background modeling and subtraction is a core component in motion analysis. The central idea behind such module is to create a probabilistic representation of the static scene tha...
Antoine Monnet, Anurag Mittal, Nikos Paragios, Vis...