Multiple hypotheses data association propagation for robust monocular-based SLAM algorithms

Mauricio Soto-Alvarez; Petri Honkamaa

doi:10.1109/ICASSP.2014.6854865

Multiple hypotheses data association propagation for robust monocular-based SLAM algorithms

Mauricio Soto-Alvarez, Petri Honkamaa

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

4 Citations (Scopus)

Abstract

Data Association is probably the most important step of every monocular Simultaneous Localization and Mapping (SLAM) algorithm because it provides the basic information to the estimation module, independently on the estimation algorithm of choice. Although important, it is also a difficult task because the analytic solution is NP-Hard. The usual approximation is obtaining only one data association hypothesis per frame which affects the robustness of the result [1][2][3][4][5]. In this paper, a data association approach is presented, where multiple hypotheses are propagated between frames using a probabilistic framework. Experimental results, using real and synthetic data, show that the proposed algorithm produces promising results with respect to other state of the art methods.

Original language	English
Title of host publication	IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014)
Publisher	IEEE Institute of Electrical and Electronic Engineers
Pages	6543-6547
ISBN (Electronic)	978-1-4799-2893-4
ISBN (Print)	978-1-4799-2892-7
DOIs	https://doi.org/10.1109/ICASSP.2014.6854865
Publication status	Published - 2014
MoE publication type	A4 Article in a conference publication
Event	IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 - Florence, Italy Duration: 4 May 2014 → 9 May 2014

Conference

Conference	IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
Abbreviated title	ICASSP 2014
Country/Territory	Italy
City	Florence
Period	4/05/14 → 9/05/14

Keywords

algorithms
localisation
mapping
data association

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10.1109/ICASSP.2014.6854865

Cite this

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title = "Multiple hypotheses data association propagation for robust monocular-based SLAM algorithms",

abstract = "Data Association is probably the most important step of every monocular Simultaneous Localization and Mapping (SLAM) algorithm because it provides the basic information to the estimation module, independently on the estimation algorithm of choice. Although important, it is also a difficult task because the analytic solution is NP-Hard. The usual approximation is obtaining only one data association hypothesis per frame which affects the robustness of the result [1][2][3][4][5]. In this paper, a data association approach is presented, where multiple hypotheses are propagated between frames using a probabilistic framework. Experimental results, using real and synthetic data, show that the proposed algorithm produces promising results with respect to other state of the art methods.",

keywords = "algorithms, localisation, mapping, data association",

author = "Mauricio Soto-Alvarez and Petri Honkamaa",

year = "2014",

doi = "10.1109/ICASSP.2014.6854865",

language = "English",

isbn = "978-1-4799-2892-7",

pages = "6543--6547",

booktitle = "IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014)",

publisher = "IEEE Institute of Electrical and Electronic Engineers",

address = "United States",

note = "IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014, ICASSP 2014 ; Conference date: 04-05-2014 Through 09-05-2014",

}

Soto-Alvarez, M & Honkamaa, P 2014, Multiple hypotheses data association propagation for robust monocular-based SLAM algorithms. in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014). IEEE Institute of Electrical and Electronic Engineers, pp. 6543-6547, IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014, Florence, Italy, 4/05/14. https://doi.org/10.1109/ICASSP.2014.6854865

Multiple hypotheses data association propagation for robust monocular-based SLAM algorithms. / Soto-Alvarez, Mauricio; Honkamaa, Petri.

IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014). IEEE Institute of Electrical and Electronic Engineers, 2014. p. 6543-6547.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - Multiple hypotheses data association propagation for robust monocular-based SLAM algorithms

AU - Soto-Alvarez, Mauricio

AU - Honkamaa, Petri

PY - 2014

Y1 - 2014

N2 - Data Association is probably the most important step of every monocular Simultaneous Localization and Mapping (SLAM) algorithm because it provides the basic information to the estimation module, independently on the estimation algorithm of choice. Although important, it is also a difficult task because the analytic solution is NP-Hard. The usual approximation is obtaining only one data association hypothesis per frame which affects the robustness of the result [1][2][3][4][5]. In this paper, a data association approach is presented, where multiple hypotheses are propagated between frames using a probabilistic framework. Experimental results, using real and synthetic data, show that the proposed algorithm produces promising results with respect to other state of the art methods.

AB - Data Association is probably the most important step of every monocular Simultaneous Localization and Mapping (SLAM) algorithm because it provides the basic information to the estimation module, independently on the estimation algorithm of choice. Although important, it is also a difficult task because the analytic solution is NP-Hard. The usual approximation is obtaining only one data association hypothesis per frame which affects the robustness of the result [1][2][3][4][5]. In this paper, a data association approach is presented, where multiple hypotheses are propagated between frames using a probabilistic framework. Experimental results, using real and synthetic data, show that the proposed algorithm produces promising results with respect to other state of the art methods.

KW - algorithms

KW - localisation

KW - mapping

KW - data association

U2 - 10.1109/ICASSP.2014.6854865

DO - 10.1109/ICASSP.2014.6854865

M3 - Conference article in proceedings

SN - 978-1-4799-2892-7

SP - 6543

EP - 6547

BT - IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014)

PB - IEEE Institute of Electrical and Electronic Engineers

T2 - IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014

Y2 - 4 May 2014 through 9 May 2014

ER -

Multiple hypotheses data association propagation for robust monocular-based SLAM algorithms

Abstract

Conference

Keywords

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