In this paper, we address the problem of learning an
adaptive appearance model for object tracking. In particular,
a class of tracking techniques called “tracking by detectionâ...
Contemporary face recognition algorithms rely on precise
localization of keypoints (corner of eye, nose etc.). Unfortunately,
finding keypoints reliably and accurately remains
a...
In this paper we propose a novel nonparametric approach
for object recognition and scene parsing using dense
scene alignment. Given an input image, we retrieve its best
matches ...
Estimating the illumination and the reflectance properties
of an object surface from a sparse set of images is an
important but inherently ill-posed problem. The problem
becomes...
Kenji Hara (Kyushu University), Ko Nishino (Drexel...
We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...