摘要
针对实验室气瓶场景提出了一种结合目标检测与文本检测识别的图像描述生成方法,用于辨识气瓶场景中的潜在危险信息,并以文本形式警示监控人员。该方法首先提取场景物体的特征与瓶身上文字的特征,而后将特征映射入多模态嵌入空间,接着使用Transformer模型生成描述结果,最后根据描述语句判断场景是否危险。实验结果表明,通过本方法生成的描述语句可以有效辨识出实验室气瓶场景中的危险物品与危险原因。
Cylinders are common equipment in the laboratory,which are characterized by large,quantity,high risk concealment and great accident harm.Therefore,cylinder supervision is very important for laboratory safety management.Video monitoring is an effective laboratory safety management means,but the monitoring videos need to be watched by specially assigned staff,and the ability of the quality of the surveillance personnel is different,so it cannot be guaranteed that they can identify dangerous information in the video pictures.Therefore,this paper proposes an image description generation method combining object detection and text recognition for the laboratory gas cylinder scene,which is used to identify the potential danger information in the cylinder scene and warn the monitoring personnel in the form of text.Firstly,the features of the scene object and the text on the cylinder body are extracted and mapped into the multi-modal embedding space.Then,Transformer structure is utilized to generate caption results.Finally,it is judged whether the scene is dangerous according to the description statement.It is shown from experimental results that the description statements generated by this method can effectively identify the dangerous substances and causes in the laboratory cylinder scene.
作者
傅煦嘉
周家乐
顾震
颜秉勇
王慧锋
FU Xujia;ZHOU Jiale;GU Zhen;YAN Bingyong;WANG Huifeng(School of Information Science and Engineering,East China University of Science and Technology,Shanghai 200237,China)
出处
《华东理工大学学报（自然科学版）》
CAS
CSCD
北大核心
2023年第3期410-418,共9页
Journal of East China University of Science and Technology
基金
青年科学基金项目(61906068)
国家重点研发计划(2018YFC1803306)。
