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» Pruning Training Sets for Learning of Object Categories
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PAMI
2012
11 years 10 months ago
Quantifying and Transferring Contextual Information in Object Detection
— Context is critical for reducing the uncertainty in object detection. However, context modelling is challenging because there are often many different types of contextual infor...
Wei-Shi Zheng, Shaogang Gong, Tao Xiang
ICMCS
2005
IEEE
182views Multimedia» more  ICMCS 2005»
14 years 1 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
ECCV
2006
Springer
14 years 9 months ago
Learning Discriminative Canonical Correlations for Object Recognition with Image Sets
Abstract. We address the problem of comparing sets of images for object recognition, where the sets may represent arbitrary variations in an object's appearance due to changin...
Tae-Kyun Kim, Josef Kittler, Roberto Cipolla
CVPR
2006
IEEE
14 years 9 months ago
Incremental learning of object detectors using a visual shape alphabet
We address the problem of multiclass object detection. Our aims are to enable models for new categories to benefit from the detectors built previously for other categories, and fo...
Andreas Opelt, Axel Pinz, Andrew Zisserman
ACCV
2007
Springer
14 years 1 months ago
Object Detection Combining Recognition and Segmentation
Abstract. We develop an object detection method combining top-down recognition with bottom-up image segmentation. There are two main steps in this method: a hypothesis generation s...
Liming Wang, Jianbo Shi, Gang Song, I-fan Shen