Towards accurate object localization with smartphones
In this study, we explore the possibility of locating remote objects via cameras together with built-in inertial sensors of off-the-shelf smartphones. Our solution, CamLoc, enables a user taking two photos of an object using a smartphone at a fixed location and immediately knowing the location of th...
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2013
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sg-smu-ink.sis_research-55262019-12-19T04:00:06Z Towards accurate object localization with smartphones SHANGGUAN, Longfei ZHOU, Zimu YANG, Zheng LIU, Kebin LI, Zhenjiang LIU, Yunhao In this study, we explore the possibility of locating remote objects via cameras together with built-in inertial sensors of off-the-shelf smartphones. Our solution, CamLoc, enables a user taking two photos of an object using a smartphone at a fixed location and immediately knowing the location of the object in global coordinates, thus facilitating myriad location-based services. Such usage is user-friendly but error prone. We devise several techniques to mitigate the errors caused by cheap and noisy sensors, upgrading the positioning accuracy to an applicable level. We prototype CamLoc on Android OS, and evaluate its performance across different scenarios with various building densities. Experiment results show that our system achieves 89 percent and 72 percent physical location mapping accuracy in rural and downtown areas, respectively, which is competitive with existing solutions. 2013-09-17T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/4523 info:doi/10.1109/TPDS.2013.236 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Software Engineering |
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Software Engineering SHANGGUAN, Longfei ZHOU, Zimu YANG, Zheng LIU, Kebin LI, Zhenjiang LIU, Yunhao Towards accurate object localization with smartphones |
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In this study, we explore the possibility of locating remote objects via cameras together with built-in inertial sensors of off-the-shelf smartphones. Our solution, CamLoc, enables a user taking two photos of an object using a smartphone at a fixed location and immediately knowing the location of the object in global coordinates, thus facilitating myriad location-based services. Such usage is user-friendly but error prone. We devise several techniques to mitigate the errors caused by cheap and noisy sensors, upgrading the positioning accuracy to an applicable level. We prototype CamLoc on Android OS, and evaluate its performance across different scenarios with various building densities. Experiment results show that our system achieves 89 percent and 72 percent physical location mapping accuracy in rural and downtown areas, respectively, which is competitive with existing solutions. |
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author |
SHANGGUAN, Longfei ZHOU, Zimu YANG, Zheng LIU, Kebin LI, Zhenjiang LIU, Yunhao |
author_facet |
SHANGGUAN, Longfei ZHOU, Zimu YANG, Zheng LIU, Kebin LI, Zhenjiang LIU, Yunhao |
author_sort |
SHANGGUAN, Longfei |
title |
Towards accurate object localization with smartphones |
title_short |
Towards accurate object localization with smartphones |
title_full |
Towards accurate object localization with smartphones |
title_fullStr |
Towards accurate object localization with smartphones |
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Towards accurate object localization with smartphones |
title_sort |
towards accurate object localization with smartphones |
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Institutional Knowledge at Singapore Management University |
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2013 |
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https://ink.library.smu.edu.sg/sis_research/4523 |
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