Desing Of The Monitoring Information Synthetical Managerment Platform And Pedestrian Detection Algorithem

Currently,with the progress of intelligent management and The development of network technology,establishing a monitoring information synthetical management platform is increasingly important.Pedestrians are the most important objects in intelligent surveillance tasks.When a pedestrian is detected,tracking module of the surveillance system will be triggered.This paper focused on the pedestrian detection algorithm and the design of the monitoring information synthetical management platform.Firstly,the historical process and current situation of monitoring information management technologies was introduced,a monitoring information synthetical management platform based on the practical experience was promoted.For the defect of traditional monitoring information management platform,the new one will solve it and meet fresh demand of practical application.In this paper,platform is established on Linux environment,an open source development environment,instead of Windows environment.Because the platform operate more reliably in Linux platform.SSL transmission technology was used to improve the safety and reliability of the data transfer,and the risk of important business information leakage is decreased.Secondly,we analyze the human detection methods in video surveillance.Considering that the HOG feature has large calculation and poor real-time results,we propose a pedestrian detection method based on CENTRIST algorithm and saliency segmentation,which alleviates the interference in tracking incurred by background regions and local motion of human's hands and feet.The background region and the main moving part of a pedestrian in the CENTRIST detection bounding box can be efficiently separated by the saliency segmentation method.Therefore,the tracking performance can be improved effectively since only the global motion of a pedestrian is computed.The experimental results show that the proposed method achieves promising tracking performance and shows applicability for a real-time intelligent surveillance system.