In this paper we pursue the task of aligning an ensemble
of images in an unsupervised manner. This task has
been commonly referred to as “congealing” in literature.
A form o...
Mark Cox, Sridha Sridharan, Simon Lucey, Jeffrey C...
Subspace segmentation is the task of segmenting data
lying on multiple linear subspaces. Its applications in
computer vision include motion segmentation in video,
structure-from...
We present a wide-baseline image matching approach
based on line segments. Line segments are clustered into
local groups according to spatial proximity. Each group is
treated as...
We address the classic problems of detection, segmenta-
tion and pose estimation of people in images with a novel
definition of a part, a poselet. We postulate two criteria
(1) ...
We use concepts from chaos theory in order to model
nonlinear dynamical systems that exhibit deterministic behavior.
Observed time series from such a system can be embedded
into...
Multilinear algebra is a powerful theoretical tool for visual
geometry, but widespread usage of traditional typographical
notation often hides its conceptual elegance and
simpli...
Visual categorization problems, such as object classification or action recognition,
are increasingly often approached using a detection strategy: a classifier function
is first ...
Minh Hoai Nguyen, Lorenzo Torresani, Fernando de l...
In recent years the Markov Random Field (MRF) has
become the de facto probabilistic model for low-level vision
applications. However, in a maximum a posteriori
(MAP) framework, ...
Oliver J. Woodford, Carsten Rother, Vladimir Kolmo...
Low-rank approximation of image collections (e.g., via
PCA) is a popular tool in many areas of computer vision.
Yet, surprisingly little is known justifying the observation
that...
This paper introduces an unsupervised color segmentation
method. The underlying idea is to segment the input
image several times, each time focussing on a different
salient part...
Michael Donoser, Martin Urschler, Martin Hirzer an...