A Moving Object Detection Algorithm Based on ORB under Dynamic Scene

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. Final...

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Vydáno v:Applied Mechanics and Materials Ročník 602-605; číslo Advanced Manufacturing and Information Engineering, Intelligent Instrumentation and Industry Development; s. 1638 - 1641
Hlavní autor: Luo, Wen Hao
Médium: Journal Article
Jazyk:angličtina
Vydáno: Zurich Trans Tech Publications Ltd 11.08.2014
Témata:
Algorithms
Dynamics
High speed
Mathematical models
Moving object recognition
Moving targets
Parameters
Transformations
RANSAC
Object Detection
Dynamic Scene
ORB
ISBN:9783038351948, 3038351946
ISSN:1660-9336, 1662-7482, 1662-7482
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Popis
Shrnutí: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.
Bibliografie:Selected, peer reviewed papers from the 2014 2nd International Conference on Precision Mechanical Instruments and Measurement Technology (ICPMIMT 2014), May 30-31, 2014, Chongqing, China
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ISBN:9783038351948
3038351946
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.602-605.1638