Scatter/Gather: a cluster-based approach to browsing large document collections
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Photobook: content-based manipulation of image databases
International Journal of Computer Vision
MULTIMEDIA '98 Proceedings of the sixth ACM international conference on Multimedia
The use of MMR, diversity-based reranking for reordering documents and producing summaries
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Multimedia Information Systems
IEEE MultiMedia
Visually Searching the Web for Content
IEEE MultiMedia
Incorporating User Preferences in Multimedia Queries
ICDT '97 Proceedings of the 6th International Conference on Database Theory
Adaptive Color-Image Embeddings for Database Navigation
ACCV '98 Proceedings of the Third Asian Conference on Computer Vision-Volume I - Volume I
Target Testing and the PicHunter Bayesian Multimedia Retrieval System
ADL '96 Proceedings of the 3rd International Forum on Research and Technology Advances in Digital Libraries
PicHunter: Bayesian Relevance Feedback for Image Retrieval
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
Uniform deterministic dictionaries
ACM Transactions on Algorithms (TALG)
Relevance feedback: a power tool for interactive content-based image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
Mining Multimedia Subjective Feedback
Journal of Intelligent Information Systems
Interactive Adaptive Movie Annotation
IEEE MultiMedia
Image Navigation: A Massively Interactive Model for Similarity Retrieval of Images
International Journal of Computer Vision - Special Issue on Content-Based Image Retrieval
Query definition using interactive saliency
MIR '03 Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval
ETP '03 Proceedings of the 2003 ACM SIGMM workshop on Experiential telepresence
User term feedback in interactive text-based image retrieval
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
An empirical investigation of user term feedback in text-based targeted image search
ACM Transactions on Information Systems (TOIS)
Visual guided navigation for image retrieval
Pattern Recognition
A novel approach for filtering junk images from google search results
MMM'08 Proceedings of the 14th international conference on Advances in multimedia modeling
Concept based interactive retrieval for social environment
Proceedings of the 2010 ACM workshop on Social, adaptive and personalized multimedia interaction and access
Hi-index | 0.00 |
Human-computer interaction is a decisive factor in effective content-based access to large image repositories. In current image retrieval systems the user refines his query by selecting example images from a relevance ranking. Since the top ranked images are all similar, user feedback often results in rearrangement of the presented images only.For better incorporation of user interaction in the retrieval process, we have developed the Filter Image Browsing method. It also uses feedback through image selection. However, it is based on differences between images rather than similarities. Filter Image Browsing presents overviews of relevant parts of the database to users. Through interaction users then zoom in on parts of the image collection. By repeatedly limiting the information space, the user quickly ends up with a small amount of relevant images. The method can easily be extended for the retrieval of multimedia objects.For evaluation of the Filter Image Browsing retrieval concept, a user simulation is applied to a pictorial database containing 10,000 images acquired from the World Wide Web by a search robot. The simulation incorporates uncertainty in the definition of the information need by users. Results show Filter Image Browsing outperforms plain interactive similarity ranking in required effort from the user. Also, the method produces predictable results for retrieval sessions, so that the user quickly knows if a successful session is possible at all. Furthermore, the simulations show the overview techniques are suited for applications such as hand-held devices where screen space is limited.