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» Object Detection Via Boosted Deformable Features
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ICCV
2009
IEEE
1821views Computer Vision» more  ICCV 2009»
14 years 10 months ago
Feature Correspondence and Deformable Object Matching via Agglomerative Correspondence Clustering
We present an efficient method for feature correspondence and object-based image matching, which exploits both photometric similarity and pairwise geometric consistency from local ...
Minsu Cho (Seoul National University), Jungmin Lee...
AAAI
2007
13 years 7 months ago
Detection of Multiple Deformable Objects using PCA-SIFT
In this paper, we address the problem of identifying and localizing multiple instances of highly deformable objects in real-time video data. We present an approach which uses PCA-...
Stefan Zickler, Alexei A. Efros
SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
11 years 7 months ago
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Xiaoxiao Shi, Jean-François Paiement, David...
ICASSP
2010
IEEE
13 years 3 months ago
Human detection in images via L1-norm Minimization Learning
In recent years, sparse representation originating from signal compressed sensing theory has attracted increasing interest in computer vision research community. However, to our b...
Ran Xu, Baochang Zhang, Qixiang Ye, Jianbin Jiao
CVPR
2004
IEEE
14 years 7 months ago
Sharing Features: Efficient Boosting Procedures for Multiclass Object Detection
We consider the problem of detecting a large number of different object classes in cluttered scenes. Traditional approaches require applying a battery of different classifiers to ...
Antonio B. Torralba, Kevin P. Murphy, William T. F...