视觉物联网下智能公交客流采集统计方法仿真  

Simulation on Statistical Method for Intelligent Bus Passenger Flow Gathering under Visual Internet of Things

作　　者：于丽梅[1] 

机构地区：[1]河北工业大学廊坊分校计算机系,河北廊坊065000

出　　处：《计算机仿真》2014年第6期187-190,共4页Computer Simulation

摘　　要：研究物联网框架下智能公交客流准确统计问题,提高统计的准确性。视觉物联网下公交客流在不同时间段内呈现较大突变性,图像采集设备采集的视觉人流图像不同帧之间的灰度差会随着客流高峰的不同形成较大变化。传统的物联网下视觉统计模型中,一旦人流图像视觉灰度差变大,或造成统计阀值过大,统计失准。提出了一种物联网环境下视觉采集估计智能公交客流采集统计方法。利用小波变换方法,对采集的公交人流图像进行特征提取,利用视觉采集估计算法,将多种群竞争机制引入到免疫算法中,对人流图像进行优化估计。从而完成物联网环境下智能公交客流采集统计。实验结果表明,引入优化模型后的物联网智能公交客流采集统计方法,提高统计的准确性。In this paper, in order to improve the accuracy of the statistics, the accurate statistics problem of intelligent public transport passenger flow under the framework of web of things was researched. Under visual internet of things, the bus passenger flow shows greater mutations in different period, which will form a larger change of grayscale difference between different frames of visual flow images along with different passenger flow peak. In this paper, we proposed a statistical estimation method for intelligent transportation passenger flow collecting by visual acquisition under the environment of internet of things. Firstly, wavelet transform method was applied in feature extraction of acquired bus passage flow image. Then we used the vision acquisition estimation algorithm to introduce the competition mechanism into multi - population immune algorithm and optimized the image flow estimates. Finally, the collection statistics of intelligence bus traffic was completed under the environment of internet of things. Experimental results show that the introduced optimization model for the internet of things smart bus passenger statistical method can improve the accuracy of the statistics.

关 键 词：视觉采集估计 公交客流 客流统计 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]