Using corpus statistics to remove redundant words in text categorization
Journal of the American Society for Information Science
VisualSEEk: a fully automated content-based image query system
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
The Journal of Machine Learning Research
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Locally adaptive metrics for clustering high dimensional data
Data Mining and Knowledge Discovery
From frequent itemsets to semantically meaningful visual patterns
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Evaluating bag-of-visual-words representations in scene classification
Proceedings of the international workshop on Workshop on multimedia information retrieval
Language modeling for bag-of-visual words image categorization
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Automatic Identification of Stop Words in Chinese Text Classification
CSSE '08 Proceedings of the 2008 International Conference on Computer Science and Software Engineering - Volume 01
Toward a higher-level visual representation for object-based image retrieval
The Visual Computer: International Journal of Computer Graphics
Visual word proximity and linguistics for semantic video indexing and near-duplicate retrieval
Computer Vision and Image Understanding
Semantics-preserving bag-of-words models for efficient image annotation
LS-MMRM '09 Proceedings of the First ACM workshop on Large-scale multimedia retrieval and mining
PCA-SIFT: a more distinctive representation for local image descriptors
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Local and global feature extraction for face recognition
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Improved SIFT-features matching for object recognition
VoCS'08 Proceedings of the 2008 international conference on Visions of Computer Science: BCS International Academic Conference
| Hi-index | 12.05 |
Local feature analysis of visual content, namely using Scale Invariant Feature Transform (SIFT) descriptors, have been deployed in the 'bag-of-visual words' model (BVW) as an effective method to represent visual content information and to enhance its classification and retrieval. The key contributions of this paper are first, a novel approach for visual words construction which takes physically spatial information, angle, and scale of keypoints into account in order to preserve semantic information of objects in visual content and to enhance the traditional bag-of-visual words, is presented. Second, a method to identify and eliminate similar key points, to form semantic visual words of high quality and to strengthen the discrimination power for visual content classification, is given. Third, an approach to discover a set of semantically similar visual words and to form visual phrases representing visual content more distinctively and leading to narrowing the semantic gap is specified.