A survey on Visual-Based Localization: On the benefit of heterogeneous data
•Comprehensive review of recent methods used for the task of Visual-Based Localization.•Explicit classification on two main categorizes of state-of-the-art works.•Discussion on the strengths and weaknesses of reviewed methods according to the type of data involved. We are surrounded by plenty of inf...
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| Published in: | Pattern recognition Vol. 74; pp. 90 - 109 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
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Elsevier Ltd
01-02-2018
Elsevier |
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| Abstract | •Comprehensive review of recent methods used for the task of Visual-Based Localization.•Explicit classification on two main categorizes of state-of-the-art works.•Discussion on the strengths and weaknesses of reviewed methods according to the type of data involved.
We are surrounded by plenty of information about our environment. From these multiple sources, numerous data could be extracted: set of images, 3D model, coloured points cloud... When classical localization devices failed (e.g. GPS sensor in cluttered environments), aforementioned data could be used within a localization framework. This is called Visual Based Localization (VBL). Due to numerous data types that can be collected from a scene, VBL encompasses a large amount of different methods. This paper presents a survey about recent methods that localize a visual acquisition system according to a known environment. We start by categorizing VBL methods into two distinct families: indirect and direct localization systems. As the localization environment is almost always dynamic, we pay special attention to methods designed to handle appearances changes occurring in a scene. Thereafter, we highlight methods exploiting heterogeneous types of data. Finally, we conclude the paper with a discussion on promising trends that could permit to a localization system to reach high precision pose estimation within an area as large as possible. |
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| AbstractList | We are surrounded by plenty of information about our environment. From these multiple sources, numerous data could be extracted: set of images, 3D model, coloured points cloud... When classical localization devices failed (e.g. GPS sensor in cluttered environments), aforementioned data could be used within a localization framework. This is called Visual Based Localization (VBL). Due to numerous data types that can be collected from a scene, VBL encompasses a large amount of different methods. This paper presents a survey about recent methods that localize a visual acquisition system according to a known environment. We start by categorizing VBL methods into two distinct families: indirect and direct localization systems. As the localization environment is almost always dynamic, we pay special attention to methods designed to handle appearances changes occurring in a scene. Thereafter, we highlight methods exploiting heterogeneous types of data. Finally, we conclude the paper with a discussion on promising trends that could permit to a localization system to reach high precision pose estimation within an area as large as possible. •Comprehensive review of recent methods used for the task of Visual-Based Localization.•Explicit classification on two main categorizes of state-of-the-art works.•Discussion on the strengths and weaknesses of reviewed methods according to the type of data involved. We are surrounded by plenty of information about our environment. From these multiple sources, numerous data could be extracted: set of images, 3D model, coloured points cloud... When classical localization devices failed (e.g. GPS sensor in cluttered environments), aforementioned data could be used within a localization framework. This is called Visual Based Localization (VBL). Due to numerous data types that can be collected from a scene, VBL encompasses a large amount of different methods. This paper presents a survey about recent methods that localize a visual acquisition system according to a known environment. We start by categorizing VBL methods into two distinct families: indirect and direct localization systems. As the localization environment is almost always dynamic, we pay special attention to methods designed to handle appearances changes occurring in a scene. Thereafter, we highlight methods exploiting heterogeneous types of data. Finally, we conclude the paper with a discussion on promising trends that could permit to a localization system to reach high precision pose estimation within an area as large as possible. |
| Author | Demonceaux, Cédric Piasco, Nathan Gouet-Brunet, Valérie Sidibé, Désiré |
| Author_xml | – sequence: 1 givenname: Nathan surname: Piasco fullname: Piasco, Nathan email: nathan.piasco@u-bourgogne.fr organization: Le2i, FRE 2005 CNRS, Arts et Métiers, Univ. Bourgogne, Franche-Comté, France – sequence: 2 givenname: Désiré surname: Sidibé fullname: Sidibé, Désiré organization: Le2i, FRE 2005 CNRS, Arts et Métiers, Univ. Bourgogne, Franche-Comté, France – sequence: 3 givenname: Cédric surname: Demonceaux fullname: Demonceaux, Cédric organization: Le2i, FRE 2005 CNRS, Arts et Métiers, Univ. Bourgogne, Franche-Comté, France – sequence: 4 givenname: Valérie surname: Gouet-Brunet fullname: Gouet-Brunet, Valérie organization: LaSTIG MATIS, IGN, ENSG, Univ. Paris-Est, F-94160 Saint-Mande, France |
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| Keywords | Visual geo-localization Image-based localization Pose estimation Camera relocalisation Camera Relocalisation |
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| SubjectTerms | Camera relocalisation Computer Science Computer Vision and Pattern Recognition Image Processing Image-based localization Pose estimation Robotics Signal and Image Processing Visual geo-localization |
| Title | A survey on Visual-Based Localization: On the benefit of heterogeneous data |
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