PBIR - perception-based image retrieval
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Support vector machine active learning for image retrieval
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
DynDex: a dynamic and non-metric space indexer
Proceedings of the tenth ACM international conference on Multimedia
Mining Image Features for Efficient Query Processing
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Similarity Search in High Dimensions via Hashing
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
CBSA: content-based soft annotation for multimodal image retrieval using Bayes point machines
IEEE Transactions on Circuits and Systems for Video Technology
Bitmap indexing method for complex similarity queries with relevance feedback
MMDB '03 Proceedings of the 1st ACM international workshop on Multimedia databases
Fotofiti: web service for photo management
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
A scalable service for photo annotation, sharing, and search
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
| Hi-index | 0.00 |
We demonstrate PBIR-MM, an integrated system that we have built for conducting multimodal image retrieval. The system combines the strengths of content-based soft annotation (CBSA), multimodal relevance feedback through active learning, and perceptual distance formulation and indexing. PBIR-MM supports multimodal query and annotation in any combination of its three basic modes: seed-by-nothing, seed-by-keywords, and seed-by-content. We demonstrate PBIR-MM on a couple of very large image sets provided by image vendors and crawled from the Internet.