Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/617504
Title: Multi-Story Indoor Floor Plan Reconstruction via Mobile Crowdsensing
Authors: Ruipeng Gao;Mingmin Zhao;Tao Ye;Fan Ye;Guojie Luo;Yizhou Wang;Kaigui Bian;Tao Wang;Xiaoming Li
subject: multi-story indoor floor plan reconstruction|mobile crowdsensing
Year: 2016
Publisher: IEEE
Abstract: The lack of floor plans is a critical reason behind the current sporadic availability of indoor localization service. Service providers have to go through effort-intensive and time-consuming business negotiations with building operators, or hire dedicated personnel to gather such data. In this paper, we propose Jigsaw, a floor plan reconstruction system that leverages crowdsensed data from mobile users. It extracts the position, size, and orientation information of individual landmark objects from images taken by users. It also obtains the spatial relation between adjacent landmark objects from inertial sensor data, then computes the coordinates and orientations of these objects on an initial floor plan. By combining user mobility traces and locations where images are taken, it produces complete floor plans with hallway connectivity, room sizes, and shapes. It also identifies different types of connection areas (e.g., escalators and stairs) between stories, and employs a refinement algorithm to correct detection errors. Our experiments on three stories of two large shopping malls show that the 90-percentile errors of positions and orientations of landmark objects are about 1~2m and 5~9°, while the hallway connectivity and connection areas between stories are 100 percent correct.
Description: 
URI: http://localhost/handle/Hannan/148154
http://localhost/handle/Hannan/617504
ISSN: 1536-1233
volume: 15
issue: 6
Appears in Collections:2016

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Title: Multi-Story Indoor Floor Plan Reconstruction via Mobile Crowdsensing
Authors: Ruipeng Gao;Mingmin Zhao;Tao Ye;Fan Ye;Guojie Luo;Yizhou Wang;Kaigui Bian;Tao Wang;Xiaoming Li
subject: multi-story indoor floor plan reconstruction|mobile crowdsensing
Year: 2016
Publisher: IEEE
Abstract: The lack of floor plans is a critical reason behind the current sporadic availability of indoor localization service. Service providers have to go through effort-intensive and time-consuming business negotiations with building operators, or hire dedicated personnel to gather such data. In this paper, we propose Jigsaw, a floor plan reconstruction system that leverages crowdsensed data from mobile users. It extracts the position, size, and orientation information of individual landmark objects from images taken by users. It also obtains the spatial relation between adjacent landmark objects from inertial sensor data, then computes the coordinates and orientations of these objects on an initial floor plan. By combining user mobility traces and locations where images are taken, it produces complete floor plans with hallway connectivity, room sizes, and shapes. It also identifies different types of connection areas (e.g., escalators and stairs) between stories, and employs a refinement algorithm to correct detection errors. Our experiments on three stories of two large shopping malls show that the 90-percentile errors of positions and orientations of landmark objects are about 1~2m and 5~9°, while the hallway connectivity and connection areas between stories are 100 percent correct.
Description: 
URI: http://localhost/handle/Hannan/148154
http://localhost/handle/Hannan/617504
ISSN: 1536-1233
volume: 15
issue: 6
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7446341.pdf2.04 MBAdobe PDFThumbnail
Preview File
Title: Multi-Story Indoor Floor Plan Reconstruction via Mobile Crowdsensing
Authors: Ruipeng Gao;Mingmin Zhao;Tao Ye;Fan Ye;Guojie Luo;Yizhou Wang;Kaigui Bian;Tao Wang;Xiaoming Li
subject: multi-story indoor floor plan reconstruction|mobile crowdsensing
Year: 2016
Publisher: IEEE
Abstract: The lack of floor plans is a critical reason behind the current sporadic availability of indoor localization service. Service providers have to go through effort-intensive and time-consuming business negotiations with building operators, or hire dedicated personnel to gather such data. In this paper, we propose Jigsaw, a floor plan reconstruction system that leverages crowdsensed data from mobile users. It extracts the position, size, and orientation information of individual landmark objects from images taken by users. It also obtains the spatial relation between adjacent landmark objects from inertial sensor data, then computes the coordinates and orientations of these objects on an initial floor plan. By combining user mobility traces and locations where images are taken, it produces complete floor plans with hallway connectivity, room sizes, and shapes. It also identifies different types of connection areas (e.g., escalators and stairs) between stories, and employs a refinement algorithm to correct detection errors. Our experiments on three stories of two large shopping malls show that the 90-percentile errors of positions and orientations of landmark objects are about 1~2m and 5~9°, while the hallway connectivity and connection areas between stories are 100 percent correct.
Description: 
URI: http://localhost/handle/Hannan/148154
http://localhost/handle/Hannan/617504
ISSN: 1536-1233
volume: 15
issue: 6
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7446341.pdf2.04 MBAdobe PDFThumbnail
Preview File