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
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
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
A Visual Vocabulary for Flower Classification
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Evaluating bag-of-visual-words representations in scene classification
Proceedings of the international workshop on Workshop on multimedia information retrieval
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
NUS-WIDE: a real-world web image database from National University of Singapore
Proceedings of the ACM International Conference on Image and Video Retrieval
On vocabulary size in bag-of-visual-words representation
PCM'10 Proceedings of the 11th Pacific Rim conference on Advances in multimedia information processing: Part I
Keyframe retrieval by keypoints: can point-to-point matching help?
CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
An experimental study on the universality of visual vocabularies
Journal of Visual Communication and Image Representation
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Bag-of-visual-words is a popular image representation and attains wide application in image processing community. While its potential has been explored in many aspects, its operation still follows a basic mode, namely for a given dataset, using k-means-like clustering methods to train a vocabulary. The vocabulary obtained this way is data dependent, i.e., with a new dataset, we must train a new vocabulary. Based on previous research on determining the optimal vocabulary size, in this paper we research on the possibility of building a universal and limited visual vocabulary with optimal performance. We analyze why such a vocabulary should exist and conduct extensive experiments on three challenging datasets to validate this hypothesis. As a consequence, we believe this work sheds a new light on finally obtaining a universal visual vocabulary of limited size which can be used with any datasets to obtain the best or near-best performance.