Background model based on intensity change similarity among pixels

Author(s):  
Satoshi Yoshinaga ◽  
Atsushi Shimada ◽  
Hajime Nagahara ◽  
Rin-ichiro Taniguchi
2018 ◽  
Vol 12 (4) ◽  
pp. 32
Author(s):  
SANTOSH DADI HARIHARA ◽  
KRISHNA MOHAN PILLUTLA GOPALA ◽  
LATHA MAKKENA MADHAVI ◽  
◽  
◽  
...  

2017 ◽  
Vol 11 (6) ◽  
pp. 488-496 ◽  
Author(s):  
Muhammad Shehzad Hanif ◽  
Shafiq Ahmad ◽  
Khurram Khurshid
Keyword(s):  

2015 ◽  
Vol 734 ◽  
pp. 463-467 ◽  
Author(s):  
Pan Pan Zhang ◽  
Chun Yang Mu ◽  
Xing Ma ◽  
Fu Lu Xu

Detection of moving object is a hot topic in computer vision. Traditionally, it is detected for every pixel in whole image by Gaussian mixture background model, which may waste more time and space. In order to improving the computational efficiency, an advanced Gaussian mixture model based on Region of Interest was proposed. Firstly, the solution finds out the most probably region where the target may turn up. And then Gaussian mixture background model is built in this area. Finally, morphological filter algorithm is used for improving integrity of the detected targets. Results show that the improved method could have a more perfect detection but no more time increasing than typical method.


2016 ◽  
Author(s):  
Song Tang ◽  
Bingshu Wang ◽  
Yong Zhao ◽  
Xuefeng Hu ◽  
Yuanzhi Gong

Author(s):  
Satoshi Yoshinaga ◽  
Atsushi Shimada ◽  
Hajime Nagahara ◽  
Rin-ichiro Taniguchi

2005 ◽  
Author(s):  
Peng Liu ◽  
Ye Tian ◽  
Jian-Lai Zhou ◽  
Frank K. Soong

2017 ◽  
Vol 12 (2) ◽  
pp. 44
Author(s):  
SANTOSH DADI HARIHARA ◽  
KRISHNA MOHAN PILLUTLA GOPALA ◽  
MAKKENA MADHAVILATHA ◽  
◽  
◽  
...  

2011 ◽  
Vol 30 (8) ◽  
pp. 1918-1922 ◽  
Author(s):  
Jun-yi Zuo ◽  
Yan Liang ◽  
Chun-hui Zhao ◽  
Quan Pan ◽  
Yong-mei Cheng ◽  
...  

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