Towards Dynamic Realtime Object Labeling in Augmented Reality

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2022-12
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American English
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IEEE
Abstract

The applicability of augmented reality (AR) is stunted by the current limitations of localization systems. In various forms, simultaneous localization and mapping (SLAM) has become a common framework for providing device localization in AR systems; however, outside of camera localization data, SLAM systems typically fail to provide additional information about the environment to consumer applications. This limits the domain of potential AR applications, as many applications will require some degree of interaction between the real and virtual worlds. One such application is object labeling for moving objects. In this work, we implement an AR moving object labeling system by utilizing LUMO-SLAM, a SLAM system that registers and localizes unknown moving objects in the environment. Test runs of the system show that moving object information provided by LUMO-SLAM is sufficient for implementing a useful moving object labeling system and potentially other real-world applications of AR.

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Troutman, B., & Tuceryan, M. (2022). Towards Dynamic Realtime Object Labeling in Augmented Reality. 2022 IEEE 2nd International Conference on Intelligent Reality (ICIR), 49–53. https://doi.org/10.1109/ICIR55739.2022.00026
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2022 IEEE 2nd International Conference on Intelligent Reality (ICIR)
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