MULTIPLE VEHICLE TRACKING USING GABOR FILTER BANK PREDICTOR

被引：0
|
作者：
Graham, James [1 ]
Celenk, Mehmet [1 ]
Willis, John [1 ]
Conley, Tom [1 ]
Eren, Haluk [2 ]
机构：
[1] Ohio Univ, Sch Elect Engn & Comp Sci, Athens, OH 45701 USA
[2] Firat Univ, TBMYO, Comp Technol Dept, Elazig, Turkey
来源：
VISAPP 2009: PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON COMPUTER VISION THEORY AND APPLICATIONS, VOL 1 | 2009年
关键词：
Multiple vehicle tracking; Change detection; Gabor filter bank predictor; Motion estimation;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents a time-varying Gabor filter bank predictor for use with vehicle tracking via surveillance video. A frame-based 2D Gabor-filter bank is selected as a primary detector for any changes in a given video frame sequence. Detected changes are localized in each frame by fitting a bounding box on the silhouette of the vehicle in the region of interest (ROI). Arbitrary motion of each vehicle is fed to a non-linear directional predictor in the time axis for estimating the location of the tracked vehicle in the next frame of the video sequence. Real-time traffic-video experimentation dictates that the cone Gabor filter structure is able to tune itself into a selected target and trace it accordingly. This property is highly desirable in the fast and accurate moving vehicle or target tracking purposes in range and intensity driven sensing.
引用
收藏
页码：632 / +
页数：2
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