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CVPR
2005
IEEE
15 years 8 months ago
Jensen-Shannon Boosting Learning for Object Recognition
In this paper, we propose a novel learning method, called Jensen-Shannon Boosting (JSBoost) and demonstrate its application to object recognition. JSBoost incorporates Jensen-Shan...
Xiangsheng Huang, Stan Z. Li, Yangsheng Wang
CVPR
2007
IEEE
16 years 4 months ago
An Exemplar Model for Learning Object Classes
We introduce an exemplar model that can learn and generate a region of interest around class instances in a training set, given only a set of images containing the visual class. T...
Ondrej Chum, Andrew Zisserman
ACCV
1998
Springer
15 years 6 months ago
Appearance Based Visual Learning and Object Recognition with Illumination Invariance
This paper describes a method for recognizing partially occluded objects under different levels of illumination brightness by using the eigenspace analysis. In our previous work, w...
Kohtaro Ohba, Yoichi Sato, Katsushi Ikeuchi
DAGSTUHL
1994
15 years 3 months ago
Function-Based Object Recognition
Functionality-based recognition systems recognize objects at the category level by reasoning about how well the objects support the expected function. Such systems naturally assoc...
Louise Stark, Kevin W. Bowyer
ICML
2007
IEEE
16 years 3 months ago
Robust mixtures in the presence of measurement errors
We develop a mixture-based approach to robust density modeling and outlier detection for experimental multivariate data that includes measurement error information. Our model is d...
Ata Kabán, Jianyong Sun, Somak Raychaudhury