@inproceedings{e70b74216c9f42c49b218e9464d278f6,
title = "Probabilistic Logic Reasoning about Traffic Scenes",
abstract = "This paper describes a probabilistic logic reasoning system for traffic scenes based on Markov logic network, whose goal is to provide a high-level interpretation of localisation and behaviour of a vehicle on the road. This information can be used by a lane assistant agent within driver assistance systems. This work adopted an egocentric viewpoint for the vision and the reasoning tasks of the vehicle and a qualitative approach to spatial representation. Results with real data indicate good performance compared to the common sense interpretation of traffic situations.",
author = "Souza, {Carlos R.C.} and Santos, {Paulo E.}",
year = "2011",
month = sep,
day = "20",
doi = "10.1007/978-3-642-23232-9_20",
language = "English",
isbn = "978-3-642-23231-2",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer ",
pages = "219--230",
booktitle = "Towards Autonomous Robotic Systems",
note = "12th Annual Conference on Towards Autonomous Robotic Systems, TAROS 2011 ; Conference date: 31-08-2011 Through 02-09-2011",
}