Modified temporal difference method for change detection

2005 ◽  
Vol 44 (2) ◽  
pp. 027001 ◽  
Author(s):  
Tsorng-Lin Chia
Keyword(s):  
Change Detection ◽  
Difference Method ◽  
Temporal Difference

scholarly journals Urban Change Detection in TerraSAR Image Using the Difference Method and SAR Coherence Coefficient

2018 ◽  
Vol 11 (3) ◽  
pp. 18-23 ◽  
Author(s):  
Zhang Xuedong ◽  
◽  
Liu Wenxi ◽  
He Shuguang ◽  
◽  
...  
Keyword(s):  
Change Detection ◽  
Difference Method ◽  
Urban Change ◽  
The Difference

scholarly journals A temporal difference method for multi-objective reinforcement learning

2017 ◽  
Vol 263 ◽  
pp. 15-25 ◽  
Author(s):  
Manuela Ruiz-Montiel ◽  
Lawrence Mandow ◽  
José-Luis Pérez-de-la-Cruz
Keyword(s):  
Reinforcement Learning ◽  
Difference Method ◽  
Temporal Difference ◽  
Multi Objective

Temporal difference method for processing dynamic speckle patterns

2010 ◽  
Vol 283 (24) ◽  
pp. 4972-4977 ◽  
Author(s):  
L. Martí-López ◽  
H. Cabrera ◽  
R.A. Martínez-Celorio ◽  
R. González-Peña
Keyword(s):  
Difference Method ◽  
Temporal Difference ◽  
Dynamic Speckle ◽  
Speckle Patterns

A ROBUST MOVING BODY RECOGNITION METHOD

2012 ◽  
Vol 11 (02) ◽  
pp. 107-114
Author(s):  
SHOUJIA WANG ◽  
WENHUI LI ◽  
BO FU ◽  
HONGYIN NI ◽  
CONG WANG
Keyword(s):  
Computer Vision ◽  
Real Time ◽  
Connected Domain ◽  
Difference Method ◽  
Recognition Accuracy ◽  
Temporal Difference ◽  
Recognition Method ◽  
Moving Body ◽  
Robust Recognition ◽  
Body Recognition

At present, moving body recognition is one of the most active areas of research in the field of computer vision and is used widely in all kinds of videos. But the recognition accuracy of these methods has changed negatively because of the complexity of the background. In this paper, we put forward a robust recognition method. First, we obtain the moving body by tripling the temporal difference method. And then we eliminate noise from these images by mathematical morphology. Finally, we use three-scanning notation method to mark and connect the connected domain. This new method is more accurate and requires less computation in real-time experiments. The experiment result also proves its robustness.

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