We present a vision-based method that assists human
navigation within unfamiliar environments. Our main contribution
is a novel algorithm that learns the correlation between
use...
This paper presents a method to quantitatively evaluate
information contributions of individual bottom-up and topdown
computing processes in object recognition. Our objective
is...
2D Active Appearance Models (AAM) and 3D Morphable
Models (3DMM) are widely used techniques. AAM
provide a fast fitting process, but may represent unwanted
3D transformations un...
We present a new variational level-set-based segmentation
formulation that uses both shape and intensity prior information
learned from a training set. By applying Bayes’
rule...
We propose a novel approach for multi-person trackingby-
detection in a particle filtering framework. In addition
to final high-confidence detections, our algorithm uses the
con...
Michael D. Breitenstein, Fabian Reichlin, Bastian ...
It has recently been shown that deformable 3D surfaces
could be recovered from single video streams. However, ex-
isting techniques either require a reference view in which
the ...
Aydin Varol, Mathieu Salzmann, Engin Tola, Pascal ...
A general framework simultaneously addressing pose
estimation, 2D segmentation, object recognition, and 3D
reconstruction from a single image is introduced in this
paper. The pr...
This paper addresses the problem of automatic temporal
annotation of realistic human actions in video using mini-
mal manual supervision. To this end we consider two asso-
ciate...
Olivier Duchenne, Ivan Laptev, Josef Sivic, Franci...
This paper presents a simple yet practical 3-D modeling
method for recovering surface shape and reflectance
from a set of images. We attach a point light source to a
hand-held c...
Many interactive image segmentation approaches use an objective function which includes appearance models as an unknown variable. Since the resulting optimization problem is NP-har...