PicPose: Using picture posing for localization service on IoT devices

Yu Meng, Kwei Jay Lin, Bo Lung Tsai, Chi Sheng Shih, Bin Zhang

研究成果: 圖書/報告稿件的類型會議稿件同行評審

3 引文 斯高帕斯(Scopus)

摘要

Device self-localization is an important capability for many IoT applications that require mobility in service capabilities. In our previous work, we have designed the ArPico method for robot indoor localization. By placing and recognizing pre-installed pictures on walls, robots can use low-cost cameras to identify their positions by referencing to pictures' precise locations. However, using ArPico, all pictures need to have clear rectangular borders for the pose computation. But some real-world pictures does not have clear thick borders. Moreover, some pictures may have odd shapes or are only partially visible. To address these problems, a new picture-based localization service PicPose is presented. PicPose relies on the feature points extracted from a camera-captured image and conducts feature point matching with the original wall picture to conduct pose calculation. Using PicPose, even partially visible pictures can be used for localization, which is impossible for ArPico and ArUco. We present our implementation and experiment results in this paper.

原文英語
主出版物標題Proceedings - 2019 IEEE 12th Conference on Service-Oriented Computing and Applications, SOCA 2019
發行者Institute of Electrical and Electronics Engineers Inc.
頁面82-89
頁數8
ISBN(電子)9781728154114
DOIs
出版狀態已出版 - 11 2019
對外發佈
事件12th IEEE Conference on Service-Oriented Computing and Applications, SOCA 2019 - Kaohsiung, 台灣
持續時間: 18 11 201921 11 2019

出版系列

名字Proceedings - 2019 IEEE 12th Conference on Service-Oriented Computing and Applications, SOCA 2019

Conference

Conference12th IEEE Conference on Service-Oriented Computing and Applications, SOCA 2019
國家/地區台灣
城市Kaohsiung
期間18/11/1921/11/19

文獻附註

Publisher Copyright:
© 2019 IEEE.

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