@inproceedings{e0e4f26453774860a01a040d2a1e6bfb,
title = "Support vector regression for surveillance purposes",
abstract = "This paper addresses the problem of applying powerful statistical pattern classification algorithm based on kernel functions to target tracking on surveillance systems. Rather than directly adapting a recognizer, we develop a localizer directly using the regression form of the Support Vector Machines (SVM). The proposed approach considers to use dynamic model together as feature vectors and makes the hyperplane and the support vectors follow the changes in these features. The performance of the tracker is demonstrated in a sensor network scenario with a constant velocity moving target on a plane for surveillance purpose.",
author = "Sedat Ozer and Cirpan, {Hakan A.} and Nihat Kabaoglu",
year = "2006",
doi = "10.1007/11848035_59",
language = "English",
isbn = "3540393927",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "442--449",
booktitle = "Multimedia Content Representation, Classification and Security - International Workshop, MRCS 2006. Proceedings",
address = "Germany",
note = "International Workshop on Multimedia Content Representation, Classification and Security, MRCS 2006 ; Conference date: 11-09-2006 Through 13-09-2006",
}