@inproceedings{cf3944f324b84a0abd732af807a33439,
title = "Automated ground-plane estimation for trajectory rectification",
abstract = "We present a system to determine ground-plane parameters in densely crowded scenes where use of geometric features such as parallel lines or reliable estimates of agent dimensions are not possible. Using feature points tracked over short intervals, together with some plausible scene assumptions, we can estimate the parameters of the ground-plane to a sufficient degree of accuracy to correct usefully for perspective distortion. This paper describes feasibility studies conducted on controlled, simulated data, to establish how different levels and types of noise affect the accuracy of the estimation, and a verification of the approach on live data, showing the method can estimate ground-plane parameters, thus allowing improved accuracy of trajectory analysis.",
keywords = "crowd-motion, ground-plane, rectification, trajectory",
author = "Ian Hales and David Hogg and Kia Ng and Roger Boyle",
year = "2013",
month = aug,
day = "7",
doi = "10.1007/978-3-642-40246-3\_47",
language = "English",
isbn = "9783642402456",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Nature",
number = "PART 2",
pages = "378--385",
booktitle = "Computer Analysis of Images and Patterns - 15th International Conference, CAIP 2013, Proceedings",
address = "Switzerland",
edition = "PART 2",
note = "15th International Conference on Computer Analysis of Images and Patterns, CAIP 2013 ; Conference date: 27-08-2013 Through 29-08-2013",
}