%0 Journal Article %1 MarquesBarenholtzCharvillat11mtaa %A Marques, Oge %A Barenholtz, Elan %A Charvillat, Vincent %D 2011 %J Multimedia Tools and Applications %K v1205 springer paper ai multimedia adaptive image video processing zzz.th %N 1 %P 303-339 %R 10.1007/s11042-010-0631-y %T Context Modeling in Computer Vision: Techniques, Implications, and Applications %V 51 %X In recent years there has been a surge of interest in context modeling for numerous applications in computer vision. The basic motivation behind these diverse efforts is generally the same---attempting to enhance current image analysis technologies by incorporating information from outside the target object, including scene analysis as well as metadata. However, many different approaches and applications have been proposed, leading to a somewhat inchoate literature that can be difficult to navigate. The current paper provides a roadmap' of this new research, including a discussion of the basic motivation behind context-modeling, an overview of the most representative techniques, and a discussion of specific applications in which contextual modeling has been incorporated. This review is intended to introduce researchers in computer vision and image analysis to this increasingly important field as well as provide a reference for those who may wish to incorporate context modeling in their own work.

@article{MarquesBarenholtzCharvillat11mtaa, abstract = {In recent years there has been a surge of interest in context modeling for numerous applications in computer vision. The basic motivation behind these diverse efforts is generally the same---attempting to enhance current image analysis technologies by incorporating information from outside the target object, including scene analysis as well as metadata. However, many different approaches and applications have been proposed, leading to a somewhat inchoate literature that can be difficult to navigate. The current paper provides a roadmap' of this new research, including a discussion of the basic motivation behind context-modeling, an overview of the most representative techniques, and a discussion of specific applications in which contextual modeling has been incorporated. This review is intended to introduce researchers in computer vision and image analysis to this increasingly important field as well as provide a reference for those who may wish to incorporate context modeling in their own work.}, added-at = {2012-05-30T10:50:32.000+0200}, author = {Marques, Oge and Barenholtz, Elan and Charvillat, Vincent}, biburl = {https://www.bibsonomy.org/bibtex/299c544aeecaff5099c4eab00d599ab2c/flint63}, doi = {10.1007/s11042-010-0631-y}, file = {SpringerLink:2011/MarquesBarenholtzCharvillat11mtaa.pdf:PDF}, groups = {public}, interhash = {b8b847dcf4005748047c8c658f32b1c1}, intrahash = {99c544aeecaff5099c4eab00d599ab2c}, issn = {1380-7501}, journal = {Multimedia Tools and Applications}, keywords = {v1205 springer paper ai multimedia adaptive image video processing zzz.th}, month = {#jan#}, number = 1, pages = {303-339}, timestamp = {2018-04-16T12:18:14.000+0200}, title = {Context Modeling in Computer Vision: Techniques, Implications, and Applications}, username = {flint63}, volume = 51, year = 2011 }