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CVPR
2012
IEEE
11 years 10 months ago
A codebook-free and annotation-free approach for fine-grained image categorization
Fine-grained categorization refers to the task of classifying objects that belong to the same basic-level class (e.g. different bird species) and share similar shape or visual app...
Bangpeng Yao, Gary R. Bradski, Fei-Fei Li
PAMI
2010
210views more  PAMI 2010»
13 years 6 months ago
Multi-Object Analysis of Volume, Pose, and Shape Using Statistical Discrimination
Abstract— One goal of statistical shape analysis is the discrimination between two populations of objects. In this paper, we present results of discriminant analysis on multi-obj...
Kevin Gorczowski, Martin Styner, Ja-Yeon Jeong, J....
NIPS
2001
13 years 9 months ago
Categorization by Learning and Combining Object Parts
We describe an algorithm for automatically learning discriminative components of objects with SVM classifiers. It is based on growing image parts by minimizing theoretical bounds ...
Bernd Heisele, Thomas Serre, Massimiliano Pontil, ...
ICCV
2007
IEEE
14 years 9 months ago
Active Learning with Gaussian Processes for Object Categorization
Discriminative methods for visual object category recognition are typically non-probabilistic, predicting class labels but not directly providing an estimate of uncertainty. Gauss...
Ashish Kapoor, Kristen Grauman, Raquel Urtasun, Tr...
CAIP
2009
Springer
211views Image Analysis» more  CAIP 2009»
14 years 2 months ago
Contextual-Guided Bag-of-Visual-Words Model for Multi-class Object Categorization
Abstract. Bag-of-words model (BOW) is inspired by the text classification problem, where a document is represented by an unsorted set of contained words. Analogously, in the objec...
Mehdi Mirza-Mohammadi, Sergio Escalera, Petia Rade...