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论文:2017,Vol:35,Issue(1):98-102 |
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引用本文： |
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卢军, 王子梁, 朱佳磊. 一种基于时-空多尺度的运动目标检测方法[J]. 西北工业大学学报 |
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Lu Jun, Wang Ziliang, Zhu Jialei. Space-Time Multiscale Based Moving Object Detection Method[J]. Northwestern polytechnical university |
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| 一种基于时-空多尺度的运动目标检测方法 |
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| 卢军1, 王子梁2, 朱佳磊1 |
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1. 西北工业大学 航海学院, 陕西 西安 710072;
2. 63961部队, 北京 100012 |
| 摘要: |
| 针对复杂背景下多运动目标检测问题，提出了一种基于时-空多尺度的运动目标检测方法。该方法特点在于目标检测前先对待检测图像进行空间多尺度运动显著性分析，定位图像中运动目标所处的运动显著性区域；然后在显著性区域内进行时间多尺度帧间差分，通过寻找最优的差分间隔来实现不同运动速度目标的检测。实验结果表明新算法能够有效降低虚警和漏检，同时具有较强的适应性和鲁棒性。 |
| 关键词:
时-空多尺度
运动显著性检测
像素
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| Space-Time Multiscale Based Moving Object Detection Method |
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| Lu Jun1, Wang Ziliang2, Zhu Jialei1 |
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1. School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China;
2. Unit 63961 of PLA, Beijing 100012, China |
| Abstract: |
| For motion detection in temporal-spatial domain, a space-time multiscale based moving object detection method was proposed, which can carry out the multiscale in spatial and temporal respectively for motion detection. We achieve multiscale in spatial by using salience detection, and use multiscale Interval-Frame Space (IFS) to deal with the motion salience regions for the end of multiscale in temporal. This method was implemented in space multiscale which reflected the significance of movement, and also in time multiscale which reflected the difference among multiscale frames in the significant region of movement. At last, experimental results show that the proposed method can reduce false alarm and false detection probability. Meanwhile, the method has strong adaptation and robustness. |
| Key words:
motion detection
space-time multiscale motion salience detection
motion significance detection
pixels
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| 收稿日期: 2016-04-01
修回日期:
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| DOI: |
| 通讯作者:
Email： |
| 作者简介: 卢军(1974-),西北工业大学博士研究生,主要从事水下航行器总体设计与综合性能分析研究。
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| 作者相关文章 |
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| 卢军 在本刊中的所有文章 |
| 王子梁 在本刊中的所有文章 |
| 朱佳磊 在本刊中的所有文章 |
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参考文献: |
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[1] Mittal A, Paragios N. Motion-Based Background Subtraction Using Adaptative Kernel Density Estimation[C]//Proc Conf Comp Vision Pattern Rec, 2004
[2] 姬莉霞,李学相. 基于相邻帧补偿的高速运动目标图像稳像算法及仿真[J]. 计算机科学,2014,41(7):310-312 Ji Lixia, Li Xuexiang. Algorithm and Simulation of Image Stabilization for High Speed Moving Target Images Based on Adjacent Frames Compensation[J]. Computer Science,2014,41(7):310-312(in Chinese)
[3] 薛丽霞,罗艳丽,王佐成. 基于帧间差分的自适应运动目标检测方法[J]. 计算机应用研究,2011,28(4):1551-1552 Xue Lixia, Luo Yanli, Wang Zuocheng. Detection Algorithm of Adaptive Moving Objects Based on Frame Difference Method[J]. Computer Application Research,2011,28(4):1551-1552(in Chinese)
[4] 宋杨. 基于高斯混合模型的运动目标检测算法研究[D]. 大连:大连理工大学,2008 Song Yang. Moving Object Detection Based on Gaussian Mixture Model[D]. Dalian, Dalian University of Technology Masteral Dissertation, 2008(in Chinese)
[5] 焦宾,吕霞付,陈勇. 一种改进的自适应高斯混合模型实时运动目标检测算法[J]. 计算机应用研究,2013,30(11):3518-3520 Jiao Bin, Lü Xiafu, Chen Yong. Improved Algorithm of Adaptive Gaussian Mixture Model for Real-Time Moving Object Detection[J].Computer Application Research,2013,30(11):3518-3520(in Chinese)
[6] Dementhon Daniel. Spatio-Temporal Segmentation of Video by Hierarchical Mean Shift Analysis[C]//Statistical Methods in Video Processing Workshop, 2002
[7] Lu Jiangbo, Lafruit Gauthier, Catthoor Francky. Fast Reliable Multi-Scale Motion Region Detection in Video Processing[C]//Speech and Signal Processing, 2007. ICASSP 2007
[8] 李文斌,周晓敏,王长松. 一种基于背景减法的运动目标检测算法[J]. 北京科技大学学报,2008,30(2):212-216 Li Wenbin, Zhou Xiaomin, Wang Changsong. Detection Algorithm of Moving Objects Based on Background Subtraction Method[J]. Journal of University of Science and Technology Beijing,2008, 30(2):212-216(in Chinese)
[9] 周俊静,段建民. 基于栅格地图的智能车辆运动目标检测[J]. 系统工程与电子技术,2015,37(2):436-442 Zhou Junjing, Duan Jianmin. Moving Object Detection for Intelligent Vehicles Based on Occupancy Grid Map[J]. System Engineering and Electronic Technology,2015,37(2):436-442(in Chinese) |
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