%0 Journal Article %1 4469875 %A Huang, T.S. %A Dagli, C.K. %A Rajaram, S. %A Chang, E.Y. %A Mandel, M.I. %A Poliner, Graham E. %A Ellis, D.P.W. %D 2008 %J Proceedings of the IEEE %K %N 4 %P 648-667 %R 10.1109/JPROC.2008.916364 %T Active Learning for Interactive Multimedia Retrieval %U http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4469875 %V 96 %X As the first decade of the 21st century comes to a close, growth in multimedia delivery infrastructure and public demand for applications built on this backbone are converging like never before. The push towards reaching truly interactive multimedia technologies becomes stronger as our media consumption paradigms continue to change. In this paper, we profile a technology leading the way in this revolution: active learning. Active learning is a strategy that helps alleviate challenges inherent in multimedia information retrieval through user interaction. We show how active learning is ideally suited for the multimedia information retrieval problem by giving an overview of the paradigm and component technologies used with special attention given to the application scenarios in which these technologies are useful. Finally, we give insight into the future of this growing field and how it fits into the larger context of multimedia information retrieval.

@article{4469875, abstract = {As the first decade of the 21st century comes to a close, growth in multimedia delivery infrastructure and public demand for applications built on this backbone are converging like never before. The push towards reaching truly interactive multimedia technologies becomes stronger as our media consumption paradigms continue to change. In this paper, we profile a technology leading the way in this revolution: active learning. Active learning is a strategy that helps alleviate challenges inherent in multimedia information retrieval through user interaction. We show how active learning is ideally suited for the multimedia information retrieval problem by giving an overview of the paradigm and component technologies used with special attention given to the application scenarios in which these technologies are useful. Finally, we give insight into the future of this growing field and how it fits into the larger context of multimedia information retrieval.}, added-at = {2014-04-24T15:58:38.000+0200}, author = {Huang, T.S. and Dagli, C.K. and Rajaram, S. and Chang, E.Y. and Mandel, M.I. and Poliner, Graham E. and Ellis, D.P.W.}, biburl = {https://www.bibsonomy.org/bibtex/2cbecb84a03a50b0b5367af242fb0539b/marcelkiesel}, doi = {10.1109/JPROC.2008.916364}, interhash = {eb3c73a43bf44d7d609a8878fa5abb80}, intrahash = {cbecb84a03a50b0b5367af242fb0539b}, issn = {0018-9219}, journal = {Proceedings of the IEEE}, keywords = {}, month = {April}, number = 4, pages = {648-667}, timestamp = {2014-04-24T15:58:38.000+0200}, title = {Active Learning for Interactive Multimedia Retrieval}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4469875}, volume = 96, year = 2008 }