DocumentCode :
3494930
Title :
Incremental sparse saliency detection
Author :
Li, Yin ; Zhou, Yue ; Xu, Lei ; Yang, Xiaochao ; Yang, Jie
Author_Institution :
Inst. of Image Process. & Pattern Recognition, Shanghai Jiaotong Univ., Shanghai, China
fYear :
2009
fDate :
7-10 Nov. 2009
Firstpage :
3093
Lastpage :
3096
Abstract :
By the guidance of attention, human visual system is able to locate objects of interest in complex scene. We propose a new visual saliency detection model for both image and video. Inspired by biological vision, saliency is defined locally. Lossy compression is adopted, where the saliency of a location is measured by the Incremental Coding Length(ICL). The ICL is computed by presenting the center patch as the sparsest linear representation of its surroundings. The final saliency map is generated by accumulating the coding length. The model is tested on both images and videos. The results indicate a reliable and robust saliency of our method.
Keywords :
computer vision; feature extraction; image representation; object detection; video coding; biological vision; human visual system; incremental coding length; lossy compression; object detection; saliency map; sparse saliency detection; sparsest linear representation; Biological system modeling; Biology computing; Humans; Image coding; Layout; Length measurement; Loss measurement; Testing; Video compression; Visual system; Incremental Coding length; Saliency Detection; Sparse Coding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2009 16th IEEE International Conference on
Conference_Location :
Cairo
ISSN :
1522-4880
Print_ISBN :
978-1-4244-5653-6
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2009.5414465
Filename :
5414465
Link To Document :
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