Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
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
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
Embedding spatial information into image content description for scene retrieval
Pattern Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A visual approach for video geocoding using bag-of-scenes
Proceedings of the 2nd ACM International Conference on Multimedia Retrieval
Domain-specific image geocoding: a case study on Virginia tech building photos
Proceedings of the 13th ACM/IEEE-CS joint conference on Digital libraries
Visual word spatial arrangement for image retrieval and classification
Pattern Recognition
Image and Vision Computing
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This paper presents a new approach to encode spatial-relationship information of visual words in the well-known visual dictionary model. The current most popular approach to describe images based on visual words is by means of bags-of-words which do not encode any spatial information. We propose a graceful way to capture spatial-relationship information of visual words that encodes the spatial arrangement of every visual word in an image. Our experiments show the importance of the spatial information of visual words for image classification and show the gain in classification accuracy when using the new method. The proposed approach creates opportunities for further improvements in image description under the visual dictionary model.