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» Boosting Object Detection Using Feature Selection
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ICIP
2006
IEEE
14 years 9 months ago
Robust Object Detection using Fast Feature Selection from Huge Feature Sets
This paper describes an efficient feature selection method that quickly selects a small subset out of a given huge feature set; for building robust object detection systems. In th...
Duy-Dinh Le, Shin'ichi Satoh
CVPR
2005
IEEE
14 years 9 months ago
Object Class Recognition Using Multiple Layer Boosting with Heterogeneous Features
We combine local texture features (PCA-SIFT), global features (shape context), and spatial features within a single multi-layer AdaBoost model of object class recognition. The fir...
Wei Zhang 0002, Bing Yu, Gregory J. Zelinsky, Dimi...
ICPR
2010
IEEE
13 years 10 months ago
Detecting Faint Compact Sources Using Local Features and a Boosting Approach
Several techniques have been proposed so far in order to perform faint compact source detection in wide field interferometric radio images. However, all these methods can easily mi...
Albert Torrent, Marta Peracaula, Xavier Llado, Jor...
CVPR
2005
IEEE
14 years 9 months ago
Online Detection and Classification of Moving Objects Using Progressively Improving Detectors
Boosting based detection methods have successfully been used for robust detection of faces and pedestrians. However, a very large amount of labeled examples are required for train...
Omar Javed, Saad Ali, Mubarak Shah
CVPR
2012
IEEE
11 years 9 months ago
Boosting algorithms for simultaneous feature extraction and selection
The problem of simultaneous feature extraction and selection, for classifier design, is considered. A new framework is proposed, based on boosting algorithms that can either 1) s...
Mohammad J. Saberian, Nuno Vasconcelos