DocumentCode
2954176
Title
Salient objects detection in time sequenced images
Author
Tian, Minghui ; Wan, Shohong ; Ji, Yan ; Yue, Lihua
Author_Institution
Dept. of Comput. Sci., Univ. of Sci. & Technol. of China, Hefei
fYear
2008
fDate
1-8 June 2008
Firstpage
321
Lastpage
326
Abstract
Salient objects detection in time sequenced images has a very important role in many applications such as surveillance systems, tracking and recognition systems, scene analysis and so on. This paper presents a novel approach for salient objects detection in time sequenced images. The approach in this paper is based on a visual saliency model which is proposed for analysis in time sequenced images. The model in this paper is based on a bottom-up visual saliency model which is presented by Itti in 1998. Multi different features are introduced to describe salient objects globally in time sequenced images. And they are combined into a single saliency map. Salient objects in time sequenced images can be detected by the final saliency map. The detection algorithm is unsupervised and fast. The results of the experiments indicate that our approach is effective and very robust to noise, blur, contrast level and brightness level.
Keywords
image sequences; object detection; bottom-up visual saliency model; salient objects detection; scene analysis; single saliency map; time sequenced images; Neural networks; Object detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location
Hong Kong
ISSN
1098-7576
Print_ISBN
978-1-4244-1820-6
Electronic_ISBN
1098-7576
Type
conf
DOI
10.1109/IJCNN.2008.4633811
Filename
4633811
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