On Eliminating Static Shadow False Alarms in Automatic Incident Detection Systems

Author

Shehata, Mohamed ; Pervez, Muzamil ; Burr, Tyson ; Cai, Jun ; Badawy, Wael ; Radmanesh, Ahmad

Author_Institution

Dept. of Electr. & Comput. Eng., Calgary Univ., Alta.

fYear

2006

fDate

2006

Firstpage

759

Lastpage

764

Abstract

This paper presents an adaptive empirical algorithm which identifies static shadows within video sequences and produces static shadow maps that are used to improve the performance of video based automatic incident detection (AID) systems. The algorithm distinguishes between static shadows and other objects using background generation, motion detection, and three static shadow filters. The proposed algorithm has been tested on streams from 9 cameras to demonstrate its detection accuracy and robustness in varying lighting conditions

Keywords

filtering theory; image motion analysis; image sequences; object detection; traffic engineering computing; video signal processing; adaptive empirical algorithm; automatic incident detection system; background generation; motion detection; static shadow false alarm; static shadow filter; static shadow map; video sequence; Cameras; Filters; Intelligent transportation systems; Motion detection; Object detection; Streaming media; Surface texture; Testing; Vehicles; Video sequences;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Transportation Systems Conference, 2006. ITSC '06. IEEE

Conference_Location

Toronto, Ont.

Print_ISBN

1-4244-0093-7

Electronic_ISBN

1-4244-0094-5

Type

conf

DOI

10.1109/ITSC.2006.1706833

Filename

1706833