Real Time Multiple Object Tracking Using Tracking Matrix

Abstract

Multi-object tracking is an important subject and challenging task in computer vision research. This article presented a method of multiple objects tracking for real-time intelligent surveillance. After object detection, using Kalman filter to predict objects' state. Then, a ldquotracking matrixrdquo is calculated based on color histogram information to establish the corresponding relationship between objects. When there is occlusion or splitting, ldquomother objectrdquo and ldquochild objectrdquo are introduced to maintain continuous and reliable tracking. Experiment results show that the proposed methods are fast and effective.