@inproceedings{e19f8649070b4dc09272a584b6efe739,
title = "Balancing robustness and information abundance via self-diagnosing in traffic surveillance video analysis",
abstract = "In this work, we propose a self-diagnosing intelligent highway surveillance system and design effective solutions different lighting and weather conditions. If tracking algorithms could work properly, performing tracking should be preferred in intelligent surveillance systems. However, it is unrealistic to segment and track each individual vehicle under all circumstances. Under congestion conditions, we propose a mechanism to estimate the traffic flow parameter via regression analysis. The experimental results have shown that the self-diagnosis ability and the modules designed for the system make the proposed system robust and reliable.",
keywords = "Intelligent Surveillance, Regression Analysis, Traffic Parameter",
author = "Cheng, {Hsu Yung} and Tsai, {Luo Wei}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 12th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2015 ; Conference date: 25-08-2015 Through 28-08-2015",
year = "2015",
month = oct,
day = "19",
doi = "10.1109/AVSS.2015.7301726",
language = "???core.languages.en_GB???",
series = "AVSS 2015 - 12th IEEE International Conference on Advanced Video and Signal Based Surveillance",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "AVSS 2015 - 12th IEEE International Conference on Advanced Video and Signal Based Surveillance",
}