DocumentCode :
3495305
Title :
On the role of context in probabilistic models of visual saliency
Author :
Bruce, Neil D B ; Kornprobst, Pierre
Author_Institution :
INRIA, Sophia Antipolis, France
fYear :
2009
fDate :
7-10 Nov. 2009
Firstpage :
3089
Lastpage :
3092
Abstract :
In recent years, many principled probabilistic definitions for the determination of visual saliency have been proposed. Moreover, there has been increased focus on the role of context in the determination of visual salience. Prior efforts have shed some light on how context may help in predicting the location of, or presence of features associated with an object in the context of detection or recognition. Nevertheless, there remains a variety of manners in which context may be exploited towards providing better judgements of salient content. In this light, we investigate the role of context in the probabilistic determination of salience while presenting a number of potential avenues for future research.
Keywords :
feature extraction; probability; feature detection; feature recognition; probabilistic models; visual saliency; Animals; Context modeling; Filters; Independent component analysis; Layout; Object detection; Proposals; Roads; Statistics; Streaming media; attention; context; image statistics; saliency;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2009 16th IEEE International Conference on
Conference_Location :
Cairo
ISSN :
1522-4880
Print_ISBN :
978-1-4244-5653-6
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2009.5414483
Filename :
5414483
Link To Document :
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