A Moving Object Detection Algorithm Based on ORB under Dynamic Scene

2014 ◽  
Vol 602-605 ◽  
pp. 1638-1641 ◽  
Author(s):  
Wen Hao Luo

In this thesis, a moving object detection algorithm under dynamic scene is proposed, which is based on ORB feature. Firstly, we extract feature points and match them by using ORB. We then obtain global motion compensation image by parameters of transformation matrix based on the RANSAC method. Finally, we use the inter-frame difference method to achieve the detection of moving targets. The high speed and accuracy of ORB feature point matching method, as well as the effectiveness of the RANSAC method for removing outliers ensure accurate calculation of parameters of affine transformation model. Combined with inter-frame difference method, foreground objects can be detected entirely. Experiment results show that the algorithm can accurately detect moving objects, and to some extent, it can solve the issue of real-time detection.

2012 ◽  
Vol 532-533 ◽  
pp. 1700-1705
Author(s):  
Xiao Yun Xiong ◽  
Bing Wang ◽  
De Xing Wang

Moving object detection and feature extraction algorithm in video sequences are discussed in this paper. There are several problems in moving object detection and extraction from outdoor video surveillance, that is, moving object detection algorithm is easily interfered by background of video monitor, the feature of moving object is difficult to extract from video source, and the vibration of picture frame in outdoor video surveillance causing by wind factors effects the incorrect extraction of the moving object. The vibration causing by wind factors was corrected and an enhancement inter-frame difference algorithm based on difference histogram threshold selection is presented in this paper. The experiment results prove that this method can detect and extract the moving object accurately and efficiently, and it can meet the needs of real-time detection.


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