交通信息与安全2024，Vol.42Issue(1)：67-75,9.DOI:10.3963/j.jssn.1674-4861.2024.01.008
基于视觉和惯性传感器的大型邮轮室内旅客身份识别方法
A Method for Indoor Passenger Identity Recognition on Large Cruise Ships Based on Vision and Inertial Sensors
摘要
Abstract
The internal structure and scenes on cruise ships are complex and the surveillance camera offers limited depth information,which makes it difficult to identify the location,heading,changes in heading,and the identity of the passengers by the traditional passenger identity recognition method(PIRM)based on a single surveillance cam-era.To fill the gap,a novel method for indoor PIRM based on vision and inertial sensors is proposed.The YOLOv5 algorithm is used to extract the bounding box of each passenger and assign the pixel coordinate for each box;the pixel coordinate is further converted into the world coordinate system fixing on the camera according to the 2D-3D coordinate transformation formula;an improved neural network model then is used to estimate the true heading an-gle of passengers in the camera coordinate system.The inertial sensor data from passengers'smartphones are col-lected to detect the acceleration of the passengers and their walking states;the true heading angle of passengers in the world geodetic system is calculated by integrating magnetic field intensity;then,the extracted visual and inertial sensor data are fused,and limited features of passengers and their relationships are encoded,including walking state,step length,relative heading angle,relative distance,so as to solve the error accumulation problem of sensor signals.A similarity calculation formula between the features is proposed based on the two multi-correlation graphs,and the Vision and Inertial Sensors Graph Matching(VIGM)algorithm is employed to solve the maximum similari-ty matrix,which could identify the same passenger in both graphs.Lastly,to validate the proposed method,four scenes on the"Yangtze River Golden 3"cruise ship are employed(including the lobby,chess room,multi-function hall,and corridor),and it is found that:the average matching accuracy(AMA)of the proposed VIGM algorithm reaches 83.9%with the 1-3 s time window;the AMA of the proposed algorithm is only 4.5%lower than the ViTag algorithm using high-cost depth cameras.The results of experiments show that the proposed PIRM and VIGM algo-rithm have low implementation costs but equivalent performance compared to the method using high-cost depth cameras on large cruise ships.关键词
室内定位/邮轮室内环境/多身份匹配/特征图模型/视觉/惯性传感器Key words
indoor positioning/indoor environment of cruise ship/multi-identity matching/feature map model/vi-sion/inertial sensors分类
交通工程引用本文复制引用
冯晓艺,马玉亭,陈聪,王一飞,刘克中,陈默子..基于视觉和惯性传感器的大型邮轮室内旅客身份识别方法[J].交通信息与安全,2024,42(1):67-75,9.基金项目
国家自然科学基金面上项目(51979216)、湖北省自然科学基金创新群体项目(2021CFA001)、湖北省自然科学基金青年项目(20221J0059)资助 （51979216）
