A Novel Method for Traffic Object Detection Based on Improved Approximated Median Filter

Jian Zhu; Hongbing Cao; Qingwei Liang

首页> 外文期刊>Journal of information and computational science >A Novel Method for Traffic Object Detection Based on Improved Approximated Median Filter

【24h】

A Novel Method for Traffic Object Detection Based on Improved Approximated Median Filter

机译：基于改进的近似中值滤波的交通目标检测新方法

获取原文

获取原文并翻译 | 示例

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

文献代查 >>

页面导航

摘要
著录项
相似文献
相关主题

摘要

Aiming at the problems that when common algorithms are adopted to detect foreground objects in traffic surveillance videos, there are more false detection results with higher memory and time cost, an algorithm based on the approximated median filter is proposed for vehicle object detection under complex traffic scenes. The algorithm, which can suppress noise effectively without setting complicated parameters, takes full advantage of the information between adjacent video frames and sets up a dynamic model of the background updating rate to adjust the background updating rate adaptively in different regions of the background. It effectively decreases the complexity of computation and solves the problem of object ghost in the background caused by slow motion of the objects during the process of the background updating. The experimental results show that the proposed algorithm not only improves the accuracy of the foreground objects detection but also improves the real-time performance of the detection.

机译：针对采用普通算法对交通监控视频中的前景物体进行检测时，错误检测结果较多，存储和时间成本较高的问题，提出了一种基于近似中值滤波的复杂交通场景下车辆物体检测算法。。该算法无需设置复杂的参数即可有效抑制噪声，它充分利用了相邻视频帧之间的信息，并建立了背景更新率的动态模型，可以在背景的不同区域自适应地调整背景更新率。它有效地降低了计算的复杂度，解决了背景更新过程中由于对象移动缓慢而导致的背景对象重影的问题。实验结果表明，该算法不仅提高了前景物体的检测精度，而且提高了检测的实时性。

著录项

来源
《Journal of information and computational science》 |2012年第8期|p.2253-2261|共9页
作者
Jian Zhu; Hongbing Cao; Qingwei Liang;
展开▼
作者单位

Key Lab of Wireless Sensor Network and Communications, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China,Wuxi Sensing Net Industrialization Research Institute, Wuxi 214135, China;

Wuxi Sensing Net Industrialization Research Institute, Wuxi 214135, China;

Key Lab of Wireless Sensor Network and Communications, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China,Wuxi Sensing Net Industrialization Research Institute, Wuxi 214135, China;

展开▼
收录信息
原文格式 PDF
正文语种 eng
中图分类
关键词
intelligent transportation system; surveillance video; moving object detection; background modeling; approximated median filter; adaptive background updating;

机译：智能交通系统;监控录像;运动物体检测;背景建模;近似中值滤波器;自适应背景更新;

相似文献

外文文献
中文文献
专利

1. Object Tracking System Using Approximate Median Filter, Kalman Filter and Dynamic Template Matching [J] . G. Mallikarjuna Rao, Ch.Satyanarayana International Journal of Intelligent Systems and Applications . 2014,第5期

机译：使用近似中值滤波器，卡尔曼滤波器和动态模板匹配的目标跟踪系统
2. A method of cross-layer fusion multi-object detection and recognition based on improved faster R-CNN model in complex traffic environment [J] . Li Cui-jin, Qu Zhong, Wang Sheng-ye, Pattern recognition letters . 2021,第May期

机译：基于复杂交通环境中改进的R-CNN模型的跨层融合多对象检测和识别方法
3. Vehicle Detection and Counting Using Adaptive Background Model Based on Approximate Median Filter and Triangulation Threshold Techniques [J] . El-Khoreby M. A., Abu-Bakar S. A. R., Mokji M. Mohd, Automatic Control and Computer Sciences . 2020,第4期

机译：基于近似中值滤波器和三角测量阈值技术的自适应背景模型的车辆检测和计数
4. Complex wavelet based moving object segmentation using approximate median filter based method for video surveillance [C] . Kushwaha Alok Kumar Singh, Srivastava Rajeev IEEE International Advance Computing Conference . 2014

机译：基于近似中值滤波的基于小波的运动目标分割方法
5. Use of Bayesian Filtering and Adaptive Learning Methods to Improve the Detection and Estimation of Pathological and Neurological Disorders [D] . Maurer, Alexander Joseph. 2016

机译：使用贝叶斯过滤和自适应学习方法来改善病理和神经障碍的检测和估算
6. Training-Based Methods for Comparison of Object Detection Methods for Visual Object Tracking [O] . Ahmad Delforouzi, Bhargav Pamarthi, Marcin Grzegorzek 2018

机译：用于视觉对象跟踪的对象检测方法比较的基于训练的方法
7. Proposed Method for Estimating Traffic Accident Risk Factors Based on Object Tracking and Behavior Prediction Using Particle Filtering [O] . Youichi NATORI, Kazuhiko KAWAMOTO, Hiroshi TAKAHASHI, 2008

机译：基于对象跟踪和行为预测使用粒子滤波来估计交通事故风险因素的提出方法
8. Improved 2-D Adaptive Lattice Filtering Algorithm and its Application toDetection of Small Objects in Correlated Clutter [R] . French, P. A., Zeidler, J. R., Ku, W. H. 1994

机译：改进的二维自适应格子滤波算法及其在相关杂波中小物体检测中的应用

A Novel Method for Traffic Object Detection Based on Improved Approximated Median Filter

摘要

著录项

相似文献

相关主题

期刊订阅