Proceedings ArticleDOI
PicPose: Using Picture Posing for Localization Service on IoT Devices
Yu Meng,Kwei-Jay Lin,Bo-Lung Tsai,Chi-Sheng Shih,Bin Zhang +4 more
- pp 82-89
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TLDR
A new picture-based localization service PicPose is presented that 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, which is impossible for ArPico and ArUco.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.read more
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Proceedings ArticleDOI
DynaScale: An Intelligent Image Scale Selection Framework for Visual Matching in Smart IoT
TL;DR: DynaScale as discussed by the authors is a general framework that integrates existing image detection and matching algorithms with constructed image pyramids for extended matching, and selects the best matching result from the image pairs of different scales.
References
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Posted Content
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Proceedings ArticleDOI
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