Multi-line fitting using two-stage iterative adaptive approach

Junli Liang; Ding Liu; Yue Zhao; Nianlong Song

doi:10.1007/978-3-642-33509-9_14

Multi-line fitting using two-stage iterative adaptive approach

Junli Liang, Ding Liu, Yue Zhao, Nianlong Song

Xi'an University of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Scopus citations

Abstract

A new multi-line fitting algorithm using two-stage iterative adaptive approach (IAA) is proposed in this paper. The key points and main contributions are: i) The proposed algorithm decouples the multi-line fitting problem into two-stage spectral estimation problems; ii) In the first stage, it formulates the binary image into virtual far-field array signals with a single snapshot, and estimates the incoming angles using the iterative adaptive approach; iii) In the second stage, it formulates the binary image into multiple near-field signals, and estimates the offsets of these lines using IAA. Simulation and experimental (lane detection) results show that the proposed algorithm is an alternative multi-line fitting approach.

Original language	English
Title of host publication	Intelligent Robotics and Applications - 5th International Conference, ICIRA 2012, Proceedings
Pages	144-153
Number of pages	10
Edition	PART 1
DOIs	https://doi.org/10.1007/978-3-642-33509-9_14
State	Published - 2012
Externally published	Yes
Event	5th International Conference on Intelligent Robotics and Applications, ICIRA 2012 - Montreal, QC, Canada Duration: 3 Oct 2012 → 5 Oct 2012

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	7506 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	5th International Conference on Intelligent Robotics and Applications, ICIRA 2012
Country/Territory	Canada
City	Montreal, QC
Period	3/10/12 → 5/10/12

Keywords

Iterative adaptive approach
Multi-Line fitting

Access to Document

10.1007/978-3-642-33509-9_14

Cite this

Liang, J., Liu, D., Zhao, Y., & Song, N. (2012). Multi-line fitting using two-stage iterative adaptive approach. In Intelligent Robotics and Applications - 5th International Conference, ICIRA 2012, Proceedings (PART 1 ed., pp. 144-153). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7506 LNAI, No. PART 1). https://doi.org/10.1007/978-3-642-33509-9_14

Liang, Junli ; Liu, Ding ; Zhao, Yue et al. / Multi-line fitting using two-stage iterative adaptive approach. Intelligent Robotics and Applications - 5th International Conference, ICIRA 2012, Proceedings. PART 1. ed. 2012. pp. 144-153 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

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title = "Multi-line fitting using two-stage iterative adaptive approach",

abstract = "A new multi-line fitting algorithm using two-stage iterative adaptive approach (IAA) is proposed in this paper. The key points and main contributions are: i) The proposed algorithm decouples the multi-line fitting problem into two-stage spectral estimation problems; ii) In the first stage, it formulates the binary image into virtual far-field array signals with a single snapshot, and estimates the incoming angles using the iterative adaptive approach; iii) In the second stage, it formulates the binary image into multiple near-field signals, and estimates the offsets of these lines using IAA. Simulation and experimental (lane detection) results show that the proposed algorithm is an alternative multi-line fitting approach.",

keywords = "Iterative adaptive approach, Multi-Line fitting",

author = "Junli Liang and Ding Liu and Yue Zhao and Nianlong Song",

year = "2012",

doi = "10.1007/978-3-642-33509-9_14",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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pages = "144--153",

booktitle = "Intelligent Robotics and Applications - 5th International Conference, ICIRA 2012, Proceedings",

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note = "5th International Conference on Intelligent Robotics and Applications, ICIRA 2012 ; Conference date: 03-10-2012 Through 05-10-2012",

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Liang, J, Liu, D, Zhao, Y & Song, N 2012, Multi-line fitting using two-stage iterative adaptive approach. in Intelligent Robotics and Applications - 5th International Conference, ICIRA 2012, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 7506 LNAI, pp. 144-153, 5th International Conference on Intelligent Robotics and Applications, ICIRA 2012, Montreal, QC, Canada, 3/10/12. https://doi.org/10.1007/978-3-642-33509-9_14

Multi-line fitting using two-stage iterative adaptive approach. / Liang, Junli; Liu, Ding; Zhao, Yue et al.
Intelligent Robotics and Applications - 5th International Conference, ICIRA 2012, Proceedings. PART 1. ed. 2012. p. 144-153 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7506 LNAI, No. PART 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - A new multi-line fitting algorithm using two-stage iterative adaptive approach (IAA) is proposed in this paper. The key points and main contributions are: i) The proposed algorithm decouples the multi-line fitting problem into two-stage spectral estimation problems; ii) In the first stage, it formulates the binary image into virtual far-field array signals with a single snapshot, and estimates the incoming angles using the iterative adaptive approach; iii) In the second stage, it formulates the binary image into multiple near-field signals, and estimates the offsets of these lines using IAA. Simulation and experimental (lane detection) results show that the proposed algorithm is an alternative multi-line fitting approach.

AB - A new multi-line fitting algorithm using two-stage iterative adaptive approach (IAA) is proposed in this paper. The key points and main contributions are: i) The proposed algorithm decouples the multi-line fitting problem into two-stage spectral estimation problems; ii) In the first stage, it formulates the binary image into virtual far-field array signals with a single snapshot, and estimates the incoming angles using the iterative adaptive approach; iii) In the second stage, it formulates the binary image into multiple near-field signals, and estimates the offsets of these lines using IAA. Simulation and experimental (lane detection) results show that the proposed algorithm is an alternative multi-line fitting approach.

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Liang J, Liu D, Zhao Y, Song N. Multi-line fitting using two-stage iterative adaptive approach. In Intelligent Robotics and Applications - 5th International Conference, ICIRA 2012, Proceedings. PART 1 ed. 2012. p. 144-153. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-642-33509-9_14

Multi-line fitting using two-stage iterative adaptive approach

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