Efficient Moving Object Segmentation Algorithm for Illumination Change in Surveillance System

2005 ◽  
pp. 812-819 ◽  
Author(s):  
Tae-Yeon Jung ◽  
Ju-Young Kim ◽  
Duk-Gyoo Kim
Keyword(s):  
Surveillance System ◽  
Object Segmentation ◽  
Moving Object ◽  
Segmentation Algorithm ◽  
Illumination Change ◽  
Moving Object Segmentation

scholarly journals Automatic Moving Object Segmentation for Freely Moving Cameras

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Yanli Wan ◽  
Xifu Wang ◽  
Hongpu Hu
Keyword(s):  
Video Processing ◽  
Surveillance System ◽  
Object Segmentation ◽  
Optimization Method ◽  
Moving Object ◽  
Transformation Model ◽  
Feature Points ◽  
Moving Object Segmentation ◽  
Point Tracking ◽  
Freely Moving

This paper proposes a new moving object segmentation algorithm for freely moving cameras which is very common for the outdoor surveillance system, the car build-in surveillance system, and the robot navigation system. A two-layer based affine transformation model optimization method is proposed for camera compensation purpose, where the outer layer iteration is used to filter the non-background feature points, and the inner layer iteration is used to estimate a refined affine model based on the RANSAC method. Then the feature points are classified into foreground and background according to the detected motion information. A geodesic based graph cut algorithm is then employed to extract the moving foreground based on the classified features. Unlike the existing global optimization or the long term feature point tracking based method, our algorithm only performs on two successive frames to segment the moving foreground, which makes it suitable for the online video processing applications. The experiment results demonstrate the effectiveness of our algorithm in both of the high accuracy and the fast speed.

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