@inbook{0e04b20addd74e0e87f1e0edc9587c0c,
title = "Automatic pedestrian detection and tracking for real-time video surveillance",
abstract = "This paper presents a method for tracking and identifying pedestrians from video images taken by a fixed camera at an entrance. A pedestrian may be totally or partially occluded in a scene for some period of time. The proposed approach uses the appearance model for the identification of pedestrians and the weighted temporal texture features. We compared the proposed method with other related methods using color and shape features, and analyzed the features' stability. Experimental results with various real video data revealed that real time pedestrian tracking and recognition is possible with increased stability over 5-15\% even under occasional occlusions in video surveillance applications.",
author = "Yang, \{Hee Deok\} and Sin, \{Bong Kee\} and Lee, \{Seong Whan\}",
year = "2003",
doi = "10.1007/3-540-44887-x\_29",
language = "English",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "242--250",
editor = "Josef Kittler and Nixon, \{Mark S.\}",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
}