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» Boosting Object Detection Using Feature Selection
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ACIVS
2008
Springer
14 years 4 months ago
"Local Rank Differences" Image Feature Implemented on GPU
A currently popular trend in object detection and pattern recognition is usage of statistical classifiers, namely AdaBoost and its modifications. The speed performance of these cla...
Lukás Polok, Adam Herout, Pavel Zemcí...
ICASSP
2011
IEEE
13 years 1 months ago
Combining generic and class-specific codebooks for object categorization and detection
Combining advantages of shape and appearance features, we propose a novel model that integrates these two complementary features into a common framework for object categorization ...
Hong Pan, Yaping Zhu, Liang-Zheng Xia, Truong Q. N...
AAAI
2006
13 years 11 months ago
Bayesian Network Based Reparameterization of Haar-like Feature
Object detection using Haar-like features is formulated as a maximum likelihood estimation. Object features are described by an arbitrary Bayesian Network (BN) of Haar-like featur...
Hirotaka Niitsuma
ECCV
2004
Springer
14 years 11 months ago
A Boosted Particle Filter: Multitarget Detection and Tracking
The problem of tracking a varying number of non-rigid objects has two major difficulties. First, the observation models and target distributions can be highly non-linear and non-Ga...
Kenji Okuma, Ali Taleghani, Nando de Freitas, Jame...
ICIP
2009
IEEE
13 years 7 months ago
Object tracking by bidirectional learning with feature selection
This paper proposes a new tracking algorithm which combines object and background information, via building object and background appearance models simultaneously by nonparametric...
Heng Wang, Xinwen Hou, Cheng-Lin Liu