Visual Landmark Based 3D Road Course Estimation with Black Box Variational Inference

Felix Trusheim; Alexandru Condurache; Alfred Mertins

doi:10.1007/978-3-319-64689-3_27

Visual Landmark Based 3D Road Course Estimation with Black Box Variational Inference

Felix Trusheim, Alexandru Condurache, Alfred Mertins

Institut für Signalverarbeitung

1 Zitat (Scopus)

Abstract

In this paper we present an approach which estimates the course of a road over long distances based on static and dynamic scene cues detected by a video camera. The approach is based on a clothoid road model, a probabilistic fusion concept as well as a fast variational inference method. Our experimental results show that the approach outperforms a state-of-the-art road marking-based method in challenging real-world driving situations.

Originalsprache	Englisch
Titel	Computer Analysis of Images and Patterns
Redakteure/-innen	Michael Felsberg, Anders Heyden, Norbert Krüger
Seitenumfang	12
Band	10424
Herausgeber (Verlag)	Springer International Publishing
Erscheinungsdatum	28.07.2017
Seiten	332-343
ISBN (Print)	978-3-319-64688-6
ISBN (elektronisch)	978-3-319-64689-3
DOIs	https://doi.org/10.1007/978-3-319-64689-3_27
Publikationsstatus	Veröffentlicht - 28.07.2017
Veranstaltung	17th International Conference on Computer Analysis of Images and Patterns - Ystad, Schweden Dauer: 22.08.2017 → 24.08.2017 Konferenznummer: 196269

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10.1007/978-3-319-64689-3_27

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Trusheim, F., Condurache, A., & Mertins, A. (2017). Visual Landmark Based 3D Road Course Estimation with Black Box Variational Inference. in M. Felsberg, A. Heyden, & N. Krüger (Hrsg.), Computer Analysis of Images and Patterns (Band 10424, S. 332-343). ( Lecture Notes in Computer Science; Band 10424 LNCS). Springer International Publishing. https://doi.org/10.1007/978-3-319-64689-3_27

@inproceedings{9f098dbfb2da469b8013303f99de184e,

title = "Visual Landmark Based 3D Road Course Estimation with Black Box Variational Inference",

abstract = "In this paper we present an approach which estimates the course of a road over long distances based on static and dynamic scene cues detected by a video camera. The approach is based on a clothoid road model, a probabilistic fusion concept as well as a fast variational inference method. Our experimental results show that the approach outperforms a state-of-the-art road marking-based method in challenging real-world driving situations.",

author = "Felix Trusheim and Alexandru Condurache and Alfred Mertins",

year = "2017",

month = jul,

day = "28",

doi = "10.1007/978-3-319-64689-3\_27",

language = "English",

isbn = "978-3-319-64688-6",

volume = "10424",

series = " Lecture Notes in Computer Science",

publisher = "Springer International Publishing",

pages = "332--343",

editor = "Michael Felsberg and Anders Heyden and Norbert Kr{\"u}ger",

booktitle = "Computer Analysis of Images and Patterns",

note = "17th International Conference on Computer Analysis of Images and Patterns, CAIP 2017 ; Conference date: 22-08-2017 Through 24-08-2017",

}

Trusheim, F, Condurache, A & Mertins, A 2017, Visual Landmark Based 3D Road Course Estimation with Black Box Variational Inference. in M Felsberg, A Heyden & N Krüger (Hrsg.), Computer Analysis of Images and Patterns. Bd. 10424, Lecture Notes in Computer Science, Bd. 10424 LNCS, Springer International Publishing, S. 332-343, 17th International Conference on Computer Analysis of Images and Patterns, Ystad, Schweden, 22.08.17. https://doi.org/10.1007/978-3-319-64689-3_27

Visual Landmark Based 3D Road Course Estimation with Black Box Variational Inference. / Trusheim, Felix; Condurache, Alexandru; Mertins, Alfred.
Computer Analysis of Images and Patterns. Hrsg. / Michael Felsberg; Anders Heyden; Norbert Krüger. Band 10424 Springer International Publishing, 2017. S. 332-343 ( Lecture Notes in Computer Science; Band 10424 LNCS).

Publikation: Kapitel in Büchern/Berichten/Konferenzbänden › Konferenzbeitrag › Begutachtung

TY - GEN

T1 - Visual Landmark Based 3D Road Course Estimation with Black Box Variational Inference

AU - Trusheim, Felix

AU - Condurache, Alexandru

AU - Mertins, Alfred

N1 - Conference code: 196269

PY - 2017/7/28

Y1 - 2017/7/28

N2 - In this paper we present an approach which estimates the course of a road over long distances based on static and dynamic scene cues detected by a video camera. The approach is based on a clothoid road model, a probabilistic fusion concept as well as a fast variational inference method. Our experimental results show that the approach outperforms a state-of-the-art road marking-based method in challenging real-world driving situations.

AB - In this paper we present an approach which estimates the course of a road over long distances based on static and dynamic scene cues detected by a video camera. The approach is based on a clothoid road model, a probabilistic fusion concept as well as a fast variational inference method. Our experimental results show that the approach outperforms a state-of-the-art road marking-based method in challenging real-world driving situations.

UR - https://www.scopus.com/pages/publications/85028516261

U2 - 10.1007/978-3-319-64689-3_27

DO - 10.1007/978-3-319-64689-3_27

M3 - Conference contribution

SN - 978-3-319-64688-6

VL - 10424

T3 - Lecture Notes in Computer Science

SP - 332

EP - 343

BT - Computer Analysis of Images and Patterns

A2 - Felsberg, Michael

A2 - Heyden, Anders

A2 - Krüger, Norbert

PB - Springer International Publishing

T2 - 17th International Conference on Computer Analysis of Images and Patterns

Y2 - 22 August 2017 through 24 August 2017

ER -

Visual Landmark Based 3D Road Course Estimation with Black Box Variational Inference

Abstract

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