NDLI: Top down scene context based visual attention model for natural images

Content Provider	IEEE Xplore Digital Library
Author	Andrushia, A.D. Thangarajan, R.
Copyright Year	2015
Description	Author affiliation: Dept. of CSE, Kongu Eng. Coll., Erode, India (Thangarajan, R.) \|\| Dept. of ECE, Karunya Univ., Coimbatore, India (Andrushia, A.D.)
Abstract	Top down image semantics play a major role in predicting where people more attend in images. In the state of computational models of human visual attention incorporate high level object detections signifying top down image semantics in a separate channel along with other bottom up saliency channels. The different occurrences of objects in a scene also to attract our attention and this interaction is ignored in recent computational models. This paper deals with the attention model which uses low, high, scene features to understand how their joint presence affects visual attention. The context based features of the scene are extracted using cause effect mechanism. The MIT bench mark data base is used in this paper. The saliency map is compared with some existing models using the performance metric of ROC and area under ROC. It seems that the scene context based saliency map gives promising results compare to the state of art models.
Starting Page	563
Ending Page	567
File Size	303815
Page Count	5
File Format	PDF
e-ISBN	9781479972258
DOI	10.1109/ECS.2015.7124971
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-02-26
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Context Visualization Computer vision Computational modeling Conferences Scene context Feature extraction Saliency map Visual attention Context modeling
Content Type	Text
Resource Type	Article

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