DocumentCode :
3424513
Title :
The Interestingness of Images
Author :
Gygli, Michael ; Grabner, Herbert ; Riemenschneider, Hayko ; Nater, Fabian ; Van Gool, Luc
Author_Institution :
Comput. Vision Lab., ETH Zurich, Zurich, Switzerland
fYear :
2013
fDate :
1-8 Dec. 2013
Firstpage :
1633
Lastpage :
1640
Abstract :
We investigate human interest in photos. Based on our own and others\´ psychophysical experiments, we identify various cues for "interestingness", namely aesthetics, unusualness and general preferences. For the ranking of retrieved images, interestingness shows to be more appropriate than cues proposed earlier. Interestingness is correlated with what people believe they will remember. This is opposed to actual memorability, which is uncorrelated to both. We introduce a set of features computationally capturing the three main aspects of visual interestingness and build an interestingness predictor from them. Its performance is shown on three datasets with varying context, reflecting the prior knowledge of the viewers.
Keywords :
content-based retrieval; image processing; image retrieval; photography; aesthetics; content-based image retrieval; general preferences; human interest; image interestingness; interestingness predictor; memorability; photos; psychophysical experiments; retrieved images ranking; unusualness; viewer knowledge; visual interestingness; Context; Correlation; Databases; Histograms; Image color analysis; Psychology; Training; Human Interest; Image Classification; Image Retrival; Interestingness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision (ICCV), 2013 IEEE International Conference on
Conference_Location :
Sydney, VIC
ISSN :
1550-5499
Type :
conf
DOI :
10.1109/ICCV.2013.205
Filename :
6751313
Link To Document :
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