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We present a novel multi-view stereo method designed
for image-based rendering that generates piecewise planar
depth maps from an unordered collection of photographs.
First a di...
Sudipta N. Sinha, Drew Steedly and Richard Szelisk...
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...
Multilinear algebra is a powerful theoretical tool for visual
geometry, but widespread usage of traditional typographical
notation often hides its conceptual elegance and
simpli...
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...
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...
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...
This paper addresses the problem of fully automated
mining of public space video data. A novel Markov Clustering
Topic Model (MCTM) is introduced which builds on
existing Dynami...