ICCV
2009
IEEE
14 years 9 months ago
2009
IEEE
We study the task of detecting the occurrence of objects in large image collections or in videos, a problem that combines aspects of content based image retrieval and object locali...
ICCV
2009
IEEE
14 years 9 months ago
2009
IEEE
Context is critical for minimising ambiguity in object de-
tection. In this work, a novel context modelling framework
is proposed without the need of any prior scene segmen-
tat...
ICCV
2009
IEEE
14 years 9 months ago
2009
IEEE
Our objective is to obtain a state-of-the art object category
detector by employing a state-of-the-art image classifier
to search for the object in all possible image subwindows....
ICCV
2009
IEEE
14 years 9 months ago
2009
IEEE
We present methods for training high quality object detectors
very quickly. The core contribution is a pair of fast
training algorithms for piece-wise linear classifiers, which
...
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Homepage CVPR
2009
IEEE
14 years 11 months ago
2009
IEEE
A variety of flexible models have been proposed to detect
objects in challenging real world scenes. Motivated
by some of the most successful techniques, we propose a
hierarchica...
CVPR
2009
IEEE
14 years 11 months ago
2009
IEEE
This paper presents an algorithm for automatically detecting and segmenting a moving object from a monocular video. Detecting and segmenting a moving object from a video with limit...
CVPR
2009
IEEE
14 years 11 months ago
2009
IEEE
Recently, we proposed marginal space learning (MSL) as
a generic approach for automatic detection of 3D anatom-
ical structures in many medical imaging modalities. To
accurately...
CVPR
2009
IEEE
14 years 11 months ago
2009
IEEE
We study the problem of object classification when training
and test classes are disjoint, i.e. no training examples of
the target classes are available. This setup has hardly be...