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