%0 Conference Paper %1 Osberger1998 %A Osberger, W. %A Maeder, A.J. %B Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on %D 1998 %K Importance Map, attention classification, computer databases, image importance, important machine perceptual regions, segmentation, vision, visual %P 701--704 vol.1 %T Automatic identification of perceptually important regions in an %V 1 %X We present a method for automatically determining the perceptual importance of different regions in an image. The algorithm is based on human visual attention and eye movement characteristics. Several features known to influence human visual attention are evaluated for each region of a segmented image to produce an importance value for each factor and region. These are combined to produce an Importance Map, which classifies each region of the image in relation to its perceptual importance. Results shown indicate that the calculated Importance Maps correlate well with human perception of visually important regions. The Importance Maps can be used in a variety of applications, including compression, machine vision, and image databases. Our technique is computationally efficient and flexible, and can easily be extended to specific applications

@inproceedings{Osberger1998, abstract = {We present a method for automatically determining the perceptual importance of different regions in an image. The algorithm is based on human visual attention and eye movement characteristics. Several features known to influence human visual attention are evaluated for each region of a segmented image to produce an importance value for each factor and region. These are combined to produce an Importance Map, which classifies each region of the image in relation to its perceptual importance. Results shown indicate that the calculated Importance Maps correlate well with human perception of visually important regions. The Importance Maps can be used in a variety of applications, including compression, machine vision, and image databases. Our technique is computationally efficient and flexible, and can easily be extended to specific applications}, added-at = {2009-09-12T19:19:34.000+0200}, author = {Osberger, W. and Maeder, A.J.}, biburl = {https://www.bibsonomy.org/bibtex/254811693655ac0972f3eb9447874263f/mozaher}, booktitle = {Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on}, file = {00711240.pdf:concept disambiguation\\context\\20070203\\00711240.pdf:PDF}, interhash = {9ca77acc171d8cb7fd8ac78a550ea985}, intrahash = {54811693655ac0972f3eb9447874263f}, keywords = {Importance Map, attention classification, computer databases, image importance, important machine perceptual regions, segmentation, vision, visual}, owner = {Mozaher}, pages = {701--704 vol.1}, timestamp = {2009-09-12T19:19:41.000+0200}, title = {Automatic identification of perceptually important regions in an}, volume = 1, year = 1998 }