DocumentCode
1861640
Title
Improved Compressive Tracking in Surveillance Scenes
Author
Huazhong Xu ; Fei Yu
Author_Institution
Sch. of Autom., Wuhan Univ. of Technol., Wuhan, China
fYear
2013
fDate
26-28 July 2013
Firstpage
869
Lastpage
873
Abstract
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.
Keywords
Kalman filters; image motion analysis; image segmentation; object detection; object tracking; Kalman filter; SILTP; ViBe background subtraction algorithm; compressive tracking; moving shadow detection; object tracking method; scale invariant local ternary pattern operator; segmentation accuracy; surveillance scenes; tracking system; Image color analysis; Kalman filters; Object tracking; Robustness; Surveillance; Target tracking; background subtraction; compressive tracking; object tracking; shadow detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Graphics (ICIG), 2013 Seventh International Conference on
Conference_Location
Qingdao
Type
conf
DOI
10.1109/ICIG.2013.176
Filename
6643793
Link To Document