PicPose: Using picture posing for localization service on IoT devices
Journal
Proceedings - 2019 IEEE 12th Conference on Service-Oriented Computing and Applications, SOCA 2019
Pages
82-89
Date Issued
2019
Author(s)
Abstract
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. ? 2019 IEEE.
Subjects
Cameras; Image matching; Internet of things; Camera-captured images; Device localization; Feature point matching; Indoor localization; Localization services; Picture matching; Precise locations; Service capability; Indoor positioning systems
Type
conference paper