TY - GEN
T1 - Predicting the memorability of natural-scene images
AU - Lu, Jiaxin
AU - Xu, Mai
AU - Wang, Zulin
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/1/4
Y1 - 2017/1/4
N2 - Recent work has shown that image memorability, in general, can be reliably predicted using some state-of-the-art features. However, all existing methods are not effective in predicting memorability of natural-scene images, far from human. In this paper, we propose a novel method to improve the effectiveness of memorability prediction for natural-scene images. Specifically, we argue that some of HSV colors have either positive or negative impact on memorability of natural-scene images in our Natural-Scene Image Memorability (NSIM) dataset. Then, we develop an HSV-based feature for memorability prediction. Finally, the HSV-based feature is combined with other efficient state-of-the-art features in our approach to predict memorability on natural-scene images. Experimental results validate the effectiveness of our method.
AB - Recent work has shown that image memorability, in general, can be reliably predicted using some state-of-the-art features. However, all existing methods are not effective in predicting memorability of natural-scene images, far from human. In this paper, we propose a novel method to improve the effectiveness of memorability prediction for natural-scene images. Specifically, we argue that some of HSV colors have either positive or negative impact on memorability of natural-scene images in our Natural-Scene Image Memorability (NSIM) dataset. Then, we develop an HSV-based feature for memorability prediction. Finally, the HSV-based feature is combined with other efficient state-of-the-art features in our approach to predict memorability on natural-scene images. Experimental results validate the effectiveness of our method.
KW - HSV
KW - Image analysis
KW - memorability
UR - https://www.scopus.com/pages/publications/85011048702
U2 - 10.1109/VCIP.2016.7805542
DO - 10.1109/VCIP.2016.7805542
M3 - 会议稿件
AN - SCOPUS:85011048702
T3 - VCIP 2016 - 30th Anniversary of Visual Communication and Image Processing
BT - VCIP 2016 - 30th Anniversary of Visual Communication and Image Processing
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE Visual Communication and Image Processing, VCIP 2016
Y2 - 27 November 2016 through 30 November 2016
ER -