Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
International Journal of Computer Vision
Video Google: A Text Retrieval Approach to Object Matching in Videos
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 12 - Volume 12
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
A Bayesian Hierarchical Model for Learning Natural Scene Categories
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
A Maximum Entropy Framework for Part-Based Texture and Object Recognition
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
The Pyramid Match Kernel: Discriminative Classification with Sets of Image Features
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Object Categorization by Learned Universal Visual Dictionary
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Scalable Recognition with a Vocabulary Tree
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Spatial Weighting for Bag-of-Features
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Representing shape with a spatial pyramid kernel
Proceedings of the 6th ACM international conference on Image and video retrieval
Evaluating bag-of-visual-words representations in scene classification
Proceedings of the international workshop on Workshop on multimedia information retrieval
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
Universal and Adapted Vocabularies for Generic Visual Categorization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Optimal Compact Codebook for Efficient Object Categorization
WACV '08 Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision
Spatial extensions to bag of visual words
Proceedings of the ACM International Conference on Image and Video Retrieval
Towards a universal and limited visual vocabulary
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part II
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Bag-of-visual-words has been shown to be a powerful image representation and attained success in many computer vision and pattern recognition applications. Usually for a given classification task, researchers choose to build a specific visual vocabulary, and the problem of building a universal visual vocabulary is rarely addressed. In this paper we conduct extensive classification experiments with three features on four image datasets and show that the visual vocabularies built from different datasets can be exchanged without apparent performance loss. Furthermore, we investigate the correlation between the visual vocabularies built from different datasets and find that they are nearly identical, which explains why they are universal across classification tasks. We believe that this work reveals what is behind the universality of visual vocabularies and narrows the gap between bag-of-visual-words and bag-of-words in text domain.