Making large-scale support vector machine learning practical
Advances in kernel methods
WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)
Discriminative distance measures for object detection
Discriminative distance measures for object detection
Performance Study of Gabor Filters and Rotation Invariant Gabor Filters
MMM '05 Proceedings of the 11th International Multimedia Modelling Conference
Learning Feature Distance Measures for Image Correspondences
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Word matching using single closed contours for indexing handwritten historical documents
International Journal on Document Analysis and Recognition
Special issue on the analysis of historical documents
International Journal on Document Analysis and Recognition
Retrieval in text collections with historic spelling using linguistic and spelling variants
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
Annotations as a Tool for Disclosing Hidden Relationships Between Illuminated Manuscripts
AI*IA '07 Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing
Learning the Relative Importance of Features in Image Data
ICDEW '07 Proceedings of the 2007 IEEE 23rd International Conference on Data Engineering Workshop
Interactive Search by Direct Manipulation of Dissimilarity Space
IEEE Transactions on Multimedia
Proceedings of the 2011 Workshop on Historical Document Imaging and Processing
Interacting with digital cultural heritage collections via annotations: the CULTURA approach
Proceedings of the 2013 ACM symposium on Document engineering
Hi-index | 0.00 |
Recent initiatives like the Million Book Project and Google Print Library Project have already archived several million books in digital format, and within a few years a significant fraction of world's books will be online. While the majority of the data will naturally be text, there will also be tens of millions of pages of images. Many of these images will defy automation annotation for the foreseeable future, but a considerable fraction of the images may be amiable to automatic annotation by algorithms that can link the historical image with a modern contemporary, with its attendant metatags. In order to perform this linking we must have a suitable distance measure which appropriately combines the relevant features of shape, color, texture and text. However the best combination of these features will vary from application to application and even from one manuscript to another. In this work we propose a simple technique to learn the distance measure by perturbing the training set in a principled way. We show the utility of our ideas on archives of manuscripts containing images from natural history and cultural artifacts.