Improved Compressive Tracking in Surveillance Scenes
Huazhong Xu, Fei Yu · 2013
In this paper we present a novel method for object tracking in surveillance scenes. We improve the 'ViBe' background subtraction algorithm by adding the scale invariant local ternary pattern operator 'SILTP' so as to detect moving shadow and increase the accuracy of segmentation. An object tracking method based on Compressive Tracking and Kalman filter by using the result of background subtraction is presented, improve the accuracy and robustness of the tracking system in surveillance scenes.