Pedestrian Detection and Tracking System Based on Intelligent Video Analysis

• 1、Information and Communication Engineering School, Harbin Engineering University, Harbin 150001

Abstract：Withthe national systematic projects of "Open District"vigorously constructed,lots of cameras and monitoring nodes are put into use,and a large number of camera and monitor node came into use, thus increased the burden on the monitoring staff, bringed the reform and upgrading of the security monitoring around smart community, among which pedestrian tracking and behavioral warning analysis highlight the important position.Therefore, the paper proposed a system about pedestrian detection and trackingbased on intelligent video analysis. Method of HOG+SVM is used to designed function of pedestrian detection, by training difficulties and using NMS rectangular frame fusion mechanism to improve the performance of the classifier, the average detection rate in the actual scenes is 41.66 ms/frame, the average accuracy rate of the detection achieves 99.49%, the average recall rate is 72.21% and the average combined effect of the detection achieves 83.67%; A tracking scheme is designed to track pedestrians based on particle filter with color feature histogram, system tests showed thatthe average tracking speed in the actual scenes maintain at 6.5-8.5 ms/frame,is able to meet the real-time tracking demands.At the same time, the system client with interactive interface is designed and developed, the research of the paper is of certain practical value to behavioral warning analysis in community video surveillance.

Keywords： Intelligent video Analysis Pedestrian Detection and Tracking HOG Features SVM Classifier Particle Filter