Title :
Real-Time Visual Saliency Detection Using Gaussian Distribution
Author :
Haoqian Wang ; Chunlong Zhang ; Xingzheng Wang
Author_Institution :
Grad. Sch. at Shenzhen, Tsinghua Univ., Shenzhen, China
fDate :
May 30 2014-June 1 2014
Abstract :
Image visual saliency detection without prior knowledge of image details is fundamental for many computer vision tasks including object recognition, image retrieval, and image segmentation. In order to achieve more accurate and quick detection, this paper proposed a novel global contrast method to generate full resolution saliency maps using Gaussian distribution model. Compared with existing methods, this developed algorithm could be implemented in real-time with a higher accuracy. After a reasonable estimation of the parameters in our method, comparison experiments were conducted with five typical algorithms, experimental results demonstrate our approach is faster than the current real time approaches and accurate in maintaining high quality.
Keywords :
Gaussian distribution; computer vision; image resolution; image retrieval; image segmentation; medical image processing; object recognition; Gaussian distribution; computer vision tasks; full resolution saliency maps; global contrast method; image details; image retrieval; image segmentation; image visual saliency detection; object recognition; real-time visual saliency detection; Computational modeling; Computer vision; Gaussian distribution; Image color analysis; Image edge detection; Real-time systems; Visualization; Gaussian Distribution; Real-Time; Visual Saliency Detection;
Conference_Titel :
Medical Biometrics, 2014 International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4799-4014-1
DOI :
10.1109/ICMB.2014.41