Enhanced Detection Technology For Shop Floor Personnel Based On Computer Vision

Workshop is the basic environment for the execution of manufacturing activities,and the staff have the characteristics of subjective initiative and movement uncertainty.The supervision of the staff has always been the most difficult part of the production activities,especially the military production lines,due to the particularity of which there are often strict requirements on the number and density of person in different areas,different operations,and different production processes in the production process.It may cause catastrophic safety-accidents in the local areas where the density of staff is too much,which threatens the safety of the staff seriously.Therefore,if real-time and accurate control of production workers in this type of workshop can be carried out,safe production can be guaranteed,so as production efficiency.This thesis takes real needs and technical difficulties of the workshop into consideration,builds the system architecture and functional modules.We propose an enhanced detection technology for staff management based on computer vision.We use workshop staff detection technology,an adaptive recognition network is proposed to detect staff smartly in the workshop.When adaptive rec-network cannot recognize the object successfully,kinematic modeling is proposed to predict the position of the disappearing target,so as to complement the missed detection and enhance the detection result.Geo-fencing is used to make multi-camera data fusion come to real,thus correcting the repeated results.The real coordinates of the staff in the workshop can be computed by figuring out the mapping relationship between the pixelcoordinate-system and the world-coordinate-system.Based on the technology above,the number and location information of the staff in the workshop can be calculated all-around.Finally,the results are synchronously displayed on the Web system.The system has been delivered to the enterprise for actual use,which greatly reduces the dependence on management staff,and successfully realizes the intelligent management of workshop staff.