DocumentCode
2465471
Title
Detecting automobiles and people for semantic video retrieval
Author
Visser, Rene ; Sebe, Nicu ; Lew, Michael S.
Author_Institution
LIACS Media Lab, Leiden Univ., Netherlands
Volume
2
fYear
2002
fDate
2002
Firstpage
733
Abstract
This paper describes a method for detecting automobiles and people in streaming or archived video. Our video object tracking system is based on Kalman filter updating of an active contour over the video sequence. We use the sequential probability ratio test (SPRT) to classify the moving objects. Results are shown of a real video sequence from a busy city intersection.
Keywords
Kalman filters; image classification; image motion analysis; image segmentation; image sequences; object detection; probability; video signal processing; Kalman filter updating; active contour; archived video; automobile detection; busy city intersection; image sequence analysis; moving object classification; moving object segmentation; people detection; semantic video retrieval; sequential probability ratio test; streaming video; video object tracking system; video sequence; Automobiles; Face detection; Image segmentation; Kalman filters; Layout; Object detection; Sequential analysis; Streaming media; Testing; Video sequences;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2002. Proceedings. 16th International Conference on
ISSN
1051-4651
Print_ISBN
0-7695-1695-X
Type
conf
DOI
10.1109/ICPR.2002.1048407
Filename
1048407
Link To Document