Matching based on local brightness is quite limited, because
small changes on local appearance invalidate the
constancy in brightness. The root of this limitation is its
treatme...
Ying Wu (Northwestern University), Jialue Fan (Nor...
Accurate denition of similarity measure is a key component
in image registration. Most commonly used intensitybased
similarity measures rely on the assumptions of independence
...
State of the art methods for image and object re-
trieval exploit both appearance (via visual words) and
local geometry (spatial extent, relative pose). In large
scale problems,...
Michal Perdoch (Czech Technical University), Ondre...
The articulated body models used to represent human motion typically have many degrees of freedom, usually expressed as joint angles that are highly correlated. T...
Andrea Fossati (EPFL), Mathieu Salzmann (Universit...
This paper deals with the problem of tracking multiple targets in a distributed network of self-configuring pan-tilt-zoom cameras. We focus on applications where events unfold over...
Local image descriptors that are highly discriminative,
computational efficient, and with low storage footprint have
long been a dream goal of computer vision research. In this
...
The matching and retrieval of 2D shapes is an important
challenge in computer vision. A large number of shape
similarity approaches have been developed, with the main
focus bein...
Xingwei Yang (Temple University), Suzan Koknar-Tez...
In this paper, we propose a novel approach for learning generic visual vocabulary. We use diffusion maps to au-tomatically learn a semantic visual vocabulary from ab-undant quantiz...
Jingen Liu (University of Central Florida), Yang Y...
In this paper, we consider the problem of categorizing
videos of dynamic textures under varying view-point. We
propose to model each video with a collection of Linear
Dynamics S...
In this work we present an approach for markerless
motion capture (MoCap) of articulated objects, which are
recorded with multiple unsynchronized moving cameras.
Instead of usin...
Bodo Rosenhahn, Hans-Peter Seidel, Juergen Gall, M...