Title :
A PFT Visual Attention Detection Model Using Bayesian Framework
Author :
Pei, Chaoke ; Gao, Li ; Wang, Donghui ; Hong, Ying
Author_Institution :
Dept. of Digital Syst. Integration Tech., CAS, Beijing, China
Abstract :
Visual attention refers to the perceptual quality that makes an object or a region pop out relative to its neighbors and seize human´s visual attention. Recently, a new fast approach based on phase spectrum of Fourier Transform (PFT) was proved to be effective and also parameter-free. In this paper, we present a novel improved saliency detection model using PFT as well as the Bayesian framework. The bottom-up saliency is gathered based on PFT in several color channels and the Bayesian framework is used to incorporate top-down information with this bottom-up saliency. Experiments show that our fast PFT-based Bayesian model achieves better and more robust results than that from the state-of-the-art.
Keywords :
Bayes methods; Fourier transforms; image colour analysis; Bayesian framework; PFT visual attention detection model; bottom-up saliency; color channel; phase spectrum of Fourier transform; saliency detection model; Bayesian methods; Color; Feature extraction; Image color analysis; Mathematical model; Strontium; Visualization;
Conference_Titel :
Image and Graphics (ICIG), 2011 Sixth International Conference on
Conference_Location :
Hefei, Anhui
Print_ISBN :
978-1-4577-1560-0
Electronic_ISBN :
978-0-7695-4541-7
DOI :
10.1109/ICIG.2011.177