Abstract
A real world reconstruction that generates cyberspace not from a computer graphics tool, but from the real world, has been one of the main issues in two different communities of robotics and computer vision under different names of Simultaneous Localization And Mapping (SLAM) and Structure from Motion (SfM). However, there have been few trials that actively integrate SLAM and SfM for possible synergy. This paper shows the real world reconstruction can be enabled through this integration. As a result, the preliminary map has been generated of which five subgoals are: Realistic view (RGB), accurate geometry (depth), applicability to multi-floor indoor building, initial classification of a possible set of objects, and full automation. To this end, an engineering framework of “Acquire-Build-Comprehend (ABC)” is proposed, through which a sensor system acquires an RGB-Depth point cloud from the real world, builds a three-dimensional map, and comprehends this map to yield the possible set of objects. Its performance is demonstrated by building a map for three levels of indoor building of which volume is 1,408 m3.
| Original language | English |
|---|---|
| Pages (from-to) | 1-12 |
| Number of pages | 12 |
| Journal | Intelligent Automation and Soft Computing |
| DOIs | |
| Publication status | Accepted/In press - 2016 Jun 7 |
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Keywords
- 3-dimensional map
- Real world reconstruction
- RGB-D
- SfM
- SLAM
ASJC Scopus subject areas
- Artificial Intelligence
- Software
- Theoretical Computer Science
- Computational Theory and Mathematics
Cite this
Towards a realistic indoor world reconstruction : preliminary results for an object-oriented 3D RGB-D mapping. / Jun, Chang Hyun; Kang, Jaehyeon; Yeon, Suyong; Choi, Hyunga; Chung, Tae Young; Doh, Nakju.
In: Intelligent Automation and Soft Computing, 07.06.2016, p. 1-12.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Towards a realistic indoor world reconstruction
T2 - preliminary results for an object-oriented 3D RGB-D mapping
AU - Jun, Chang Hyun
AU - Kang, Jaehyeon
AU - Yeon, Suyong
AU - Choi, Hyunga
AU - Chung, Tae Young
AU - Doh, Nakju
PY - 2016/6/7
Y1 - 2016/6/7
N2 - A real world reconstruction that generates cyberspace not from a computer graphics tool, but from the real world, has been one of the main issues in two different communities of robotics and computer vision under different names of Simultaneous Localization And Mapping (SLAM) and Structure from Motion (SfM). However, there have been few trials that actively integrate SLAM and SfM for possible synergy. This paper shows the real world reconstruction can be enabled through this integration. As a result, the preliminary map has been generated of which five subgoals are: Realistic view (RGB), accurate geometry (depth), applicability to multi-floor indoor building, initial classification of a possible set of objects, and full automation. To this end, an engineering framework of “Acquire-Build-Comprehend (ABC)” is proposed, through which a sensor system acquires an RGB-Depth point cloud from the real world, builds a three-dimensional map, and comprehends this map to yield the possible set of objects. Its performance is demonstrated by building a map for three levels of indoor building of which volume is 1,408 m3.
AB - A real world reconstruction that generates cyberspace not from a computer graphics tool, but from the real world, has been one of the main issues in two different communities of robotics and computer vision under different names of Simultaneous Localization And Mapping (SLAM) and Structure from Motion (SfM). However, there have been few trials that actively integrate SLAM and SfM for possible synergy. This paper shows the real world reconstruction can be enabled through this integration. As a result, the preliminary map has been generated of which five subgoals are: Realistic view (RGB), accurate geometry (depth), applicability to multi-floor indoor building, initial classification of a possible set of objects, and full automation. To this end, an engineering framework of “Acquire-Build-Comprehend (ABC)” is proposed, through which a sensor system acquires an RGB-Depth point cloud from the real world, builds a three-dimensional map, and comprehends this map to yield the possible set of objects. Its performance is demonstrated by building a map for three levels of indoor building of which volume is 1,408 m3.
KW - 3-dimensional map
KW - Real world reconstruction
KW - RGB-D
KW - SfM
KW - SLAM
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U2 - 10.1080/10798587.2016.1186890
DO - 10.1080/10798587.2016.1186890
M3 - Article
AN - SCOPUS:84976309715
SP - 1
EP - 12
JO - Intelligent Automation and Soft Computing
JF - Intelligent Automation and Soft Computing
SN - 1079-8587
ER -