A survey of browsing models for content based image retrieval Export

@article{citeulike:6077060, abstract = {Abstract\ \ The problem of content based image retrieval (CBIR) has traditionally been investigated within a framework that emphasises the explicit formulation of a query: users initiate an automated search for relevant images by submitting an image or draw a sketch that exemplifies their information need. Often, relevance feedback is incorporated as a post-retrieval step for optimising the way evidence from different visual features is combined. While this sustained methodological focus has helped CBIR to mature, it has also brought out its limitations more clearly: There is often little support for exploratory search and scaling to very large collections is problematic. Moreover, the assumption that users are always able to formulate an appropriate query is questionable. An effective, albeit much less studied, method of accessing image collections based on visual content is that of browsing. The aim of this survey paper is to provide a structured overview of the different models that have been explored over the last one to two decades, to highlight the particular challenges of the browsing approach and to focus attention on a few interesting issues that warrant more intense research.}, author = {Heesch, Daniel}, citeulike-article-id = {6077060}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/s11042-008-0207-2}, citeulike-linkout-1 = {http://www.springerlink.com/content/m8x1567r331g2405}, day = {1}, doi = {10.1007/s11042-008-0207-2}, journal = {Multimedia Tools and Applications}, keywords = {2008, browsing, images, interaction, relevance-feedback, survey}, month = {November}, number = {2}, pages = {261--284}, posted-at = {2009-11-05 22:12:11}, priority = {5}, title = {A survey of browsing models for content based image retrieval}, url = {http://dx.doi.org/10.1007/s11042-008-0207-2}, volume = {40}, year = {2008} }

TY - JOUR ID - citeulike:6077060 L3 - citeulike-article-id:6077060 N2 - Abstract  The problem of content based image retrieval (CBIR) has traditionally been investigated within a framework that emphasises the explicit formulation of a query: users initiate an automated search for relevant images by submitting an image or draw a sketch that exemplifies their information need. Often, relevance feedback is incorporated as a post-retrieval step for optimising the way evidence from different visual features is combined. While this sustained methodological focus has helped CBIR to mature, it has also brought out its limitations more clearly: There is often little support for exploratory search and scaling to very large collections is problematic. Moreover, the assumption that users are always able to formulate an appropriate query is questionable. An effective, albeit much less studied, method of accessing image collections based on visual content is that of browsing. The aim of this survey paper is to provide a structured overview of the different models that have been explored over the last one to two decades, to highlight the particular challenges of the browsing approach and to focus attention on a few interesting issues that warrant more intense research. IS - 2 JF - Multimedia Tools and Applications EP - 284 TI - A survey of browsing models for content based image retrieval VL - 40 SP - 261 KW - 2008 KW - browsing KW - images KW - interaction KW - relevance-feedback KW - survey AU - Heesch, Daniel PY - 2008/11/01/ UR - http://dx.doi.org/10.1007/s11042-008-0207-2 ER -