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...
Median-shift is a mode seeking algorithm that relies on
computing the median of local neighborhoods, instead of
the mean. We further combine median-shift with Locality
Sensitive...
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...
This paper investigates the design of a system for recognizing
objects in 3D point clouds of urban environments.
The system is decomposed into four steps: locating, segmenting,
...
Aleksey Golovinskiy, Vladimir G. Kim, Thomas Funkh...