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» Multi-block PCA method for image change detection
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ICIAP
2003
ACM
13 years 10 months ago
Multi-block PCA method for image change detection
Principal component analyses (PCA) has been widely used in reduction of the dimensionality of datasets, classification, feature extraction, etc. It has been combined with many oth...
B. Qiu, Véronique Prinet, Edith Perrier, Ol...
ICB
2007
Springer
683views Biometrics» more  ICB 2007»
13 years 11 months ago
Face Detection Based on Multi-Block LBP Representation
Effective and real-time face detection has been made possible by using the method of rectangle Haar-like features with AdaBoost learning since Viola and Jones’ work [12]. In this...
Lun Zhang, Rufeng Chu, Shiming Xiang, ShengCai Lia...
ICMCS
2005
IEEE
182views Multimedia» more  ICMCS 2005»
13 years 10 months ago
An integrated approach for generic object detection using kernel PCA and boosting
In this paper we present a novel framework for generic object class detection by integrating Kernel PCA with AdaBoost. The classifier obtained in this way is invariant to changes...
Saad Ali, Mubarak Shah
PRL
2010
97views more  PRL 2010»
12 years 11 months ago
A support vector domain method for change detection in multitemporal images
Francesca Bovolo, Gustavo Camps-Valls, Lorenzo Bru...
ICCV
2005
IEEE
14 years 6 months ago
A Supervised Learning Framework for Generic Object Detection in Images
In recent years Kernel Principal Component Analysis (Kernel PCA) has gained much attention because of its ability to capture nonlinear image features, which are particularly impor...
Saad Ali, Mubarak Shah