ICCV
2009
IEEE
15 years 3 months ago
2009
IEEE
Object tracking typically relies on a dynamic model to
predict the object’s location from its past trajectory. In
crowded scenarios a strong dynamic model is particularly
impo...
ICCV
2009
IEEE
15 years 3 months ago
2009
IEEE
In this paper, we investigate the detection of semantic
human actions in complex scenes. Unlike conventional
action recognition in well-controlled environments,
action detection...
ICCV
2009
IEEE
15 years 3 months ago
2009
IEEE
The classical approach to depth from defocus uses two
images taken with circular apertures of different sizes. We
show in this paper that the use of a circular aperture
severely...
ICCV
2009
IEEE
15 years 3 months ago
2009
IEEE
High-level, or holistic, scene understanding involves
reasoning about objects, regions, and the 3D relationships
between them. This requires a representation above the
level of ...
ICCV
2009
IEEE
15 years 3 months ago
2009
IEEE
User-provided object bounding box is a simple and
popular interaction paradigm considered by many existing
interactive image segmentation frameworks. However,
these frameworks t...
ICCV
2009
IEEE
15 years 3 months ago
2009
IEEE
This purely theoretical work investigates the problem
of artificial singularities in camera self-calibration. Selfcalibration
allows one to upgrade a projective reconstruction
t...
ICCV
2009
IEEE
15 years 3 months ago
2009
IEEE
Prominent feature point descriptors such as SIFT and
SURF allow reliable real-time matching but at a compu-
tational cost that limits the number of points that can be
handled on...
ICCV
2009
IEEE
15 years 3 months ago
2009
IEEE
This paper is focused on the Co-segmentation problem
[1] – where the objective is to segment a similar object from
a pair of images. The background in the two images may be
ar...
ICCV
2009
IEEE
15 years 3 months ago
2009
IEEE
Object class models trained on hundreds or thousands of
images have shown to enable robust detection. Transferring
knowledge from such models to new object classes trained
from ...
ICCV
2009
IEEE
15 years 3 months ago
2009
IEEE
Mean shift clustering is a powerful unsupervised data
analysis technique which does not require prior knowledge
of the number of clusters, and does not constrain the shape
of th...