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Symmetry 2019, 11(1), 34; https://doi.org/10.3390/sym11010034

Moving Object Detection Using an Object Motion Reflection Model of Motion Vectors

Department of Electrical Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon-gu, Seoul 01897, Korea
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Received: 8 November 2018 / Revised: 25 December 2018 / Accepted: 26 December 2018 / Published: 2 January 2019
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Abstract

Moving object detection task can be solved by the background subtraction algorithm if the camera is fixed. However, because the background moves, detecting moving objects in a moving car is a difficult problem. There were attempts to detect moving objects using LiDAR or stereo cameras, but when the car moved, the detection rate decreased. We propose a moving object detection algorithm using an object motion reflection model of motion vectors. The proposed method first obtains the disparity map by searching the corresponding region between stereo images. Then, we estimate road by applying v-disparity method to the disparity map. The optical flow is used to acquire the motion vectors of symmetric pixels between adjacent frames where the road has been removed. We designed a probability model of how much the local motion is reflected in the motion vector to determine if the object is moving. We have experimented with the proposed method on two datasets, and confirmed that the proposed method detects moving objects with higher accuracy than other methods. View Full-Text
Keywords: object motion detection; ego-motion; optical flow; stereo matching; RANdom SAmple Consensus (RANSAC) object motion detection; ego-motion; optical flow; stereo matching; RANdom SAmple Consensus (RANSAC)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Yoo, J.; Lee, G.-C. Moving Object Detection Using an Object Motion Reflection Model of Motion Vectors. Symmetry 2019, 11, 34.

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