Title :
Salient object detection via background contrast
Author :
Quan Zhou ; Nianyi Li ; Jianxin Chen ; Shu Cai ; Latecki, Longin Jan
Author_Institution :
Key Lab. of Minist. of Educ. for Broad Band Commun. & Sensor Network Technol., Nanjing Univ. of Posts & Telecommun., Nanjing, China
Abstract :
This paper addresses the problem of salient object detection. We introduce a novel framework which aims to automatically identify salient regions in natural images based on two key ideas. The first one is to consider the statistical spatial distribution of saliency and non-saliency regions as two complementary processes. The second one is based on the assumption that contrast saliency with respect to background regions outperforms those with respect to entire image. Experimental results demonstrate the effectiveness of our approach over 12 state-of-the-art models.
Keywords :
object detection; statistical analysis; background contrast; identify salient regions; natural images; salient object detection; statistical spatial distribution; Distribution functions; Graphical models; Image color analysis; Image segmentation; Object detection; Sun; Visualization; background contrast; salient object detection; spatial distribution;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on
Conference_Location :
South Brisbane, QLD
DOI :
10.1109/ICASSP.2015.7178213