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

页码：632 / +

页数：2

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