19 search results - page 1 / 4 » Gradient Feature Selection for Online Boosting |
ICCV
2007
IEEE
15 years 25 days ago
2007
IEEE
Boosting has been widely applied in computer vision, especially after Viola and Jones's seminal work [23]. The marriage of rectangular features and integral-imageenabled fast...
ICCCN
2007
IEEE
13 years 11 months ago
2007
IEEE
In this paper, a novel feature selection algorithm for object tracking is proposed. This algorithm performs more robust than the previous works by taking the correlation between f...
ICIP
2010
IEEE
13 years 8 months ago
2010
IEEE
Co-occurrence histograms of oriented gradients (CoHOG) are powerful descriptors in object detection. In this paper, we propose to utilize a very large pool of CoHOG features with ...
ICPR
2008
IEEE
15 years 2 days ago
2008
IEEE
Online Boosting is an effective incremental learning method which can update weak classifiers efficiently according to the object being trackedt. It is a promising technique for o...
IBPRIA
2009
Springer
14 years 3 months ago
2009
Springer
The present paper addresses pedestrian detection using local boosted features that are learned from a small set of training images. Our contribution is to use two boosting steps. T...