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
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;
Conference_Titel :
Image Processing (ICIP), 2009 16th IEEE International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4244-5653-6
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2009.5414483