A spatial knowledge structure for image information systems using symbolic projections
ACM '86 Proceedings of 1986 ACM Fall joint computer conference
ImageMap: An Image Indexing Method Based on Spatial Similarity
IEEE Transactions on Knowledge and Data Engineering
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
Image Database Design Based on 9D-SPA Representation for Spatial Relations
IEEE Transactions on Knowledge and Data Engineering
Hierarchical Part-Based Visual Object Categorization
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Discovering Objects and their Localization in Images
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
Discriminative Object Class Models of Appearance and Shape by Correlatons
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
Image retrieval: Ideas, influences, and trends of the new age
ACM Computing Surveys (CSUR)
Object retrieval using configurations of salient regions
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Local invariant feature detectors: a survey
Foundations and Trends® in Computer Graphics and Vision
Spatial extensions to bag of visual words
Proceedings of the ACM International Conference on Image and Video Retrieval
Improving Bag-of-Features for Large Scale Image Search
International Journal of Computer Vision
Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Weighted walkthroughs between extended entities for retrieval by spatial arrangement
IEEE Transactions on Multimedia
From local features to local regions
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Encoding spatial arrangement of visual words
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Toward a higher-level visual representation for content-based image retrieval
Multimedia Tools and Applications
SIFT match verification by geometric coding for large-scale partial-duplicate web image search
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
A shape-based approach for leaf classification using multiscaletriangular representation
Proceedings of the 3rd ACM conference on International conference on multimedia retrieval
Visual word spatial arrangement for image retrieval and classification
Pattern Recognition
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This article presents @D-TSR, an image content representation describing the spatial layout with triangular relationships of visual entities, which can be symbolic objects or low-level visual features. A semi-local implementation of @D-TSR is also proposed, making the description robust to viewpoint changes. We evaluate @D-TSR for image retrieval under the query-by-example paradigm, on contents represented with interest points in a bag-of-features model: it improves state-of-the-art techniques, in terms of retrieval quality as well as of execution time, and is scalable. Finally, its effectiveness is evaluated on a topical scenario dedicated to scene retrieval in datasets of city landmarks.