Photo-realistic 3D model based accurate visual positioning system for large-scale indoor spaces

Hyeon, Janghun; Jang, Bumchul; Choi, Hong Soo; Kim, Joohyung; Kim, Dongwoo; Doh, Nakju Lett

doi:10.1016/j.engappai.2023.106256

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2024

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Cited by 3 publications

References 29 publications

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Understanding Red Wine Quality with Feature Importance in Machine Learning and Explainable AI

John,

Damodar,

Mohith

et al. 2024

2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)

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Understanding Red Wine Quality with Feature Importance in Machine Learning and Explainable AI

John,

Damodar,

Mohith

et al. 2024

2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)

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Smartphone Photography Visual Localization Based on an Improved Siamese Neural Network

Pu,

Cai,

Zhou

et al. 2024

IEEE Internet Things J.

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A New Approach to Reduce the Position Data of Moving Objects Using Neural Network

Diri,

Yildirim

2024

Transactions in GIS

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In this study, an ANN‐based Global Navigation Satellite System (GNSS) location data reduction approach was proposed. As GNSS location data becomes more common, efficient data reduction techniques are needed to reduce transmission, storage, and processing costs. This involves selecting key points from the original trajectory to maintain integrity, eliminating redundancy, and lowering transmission and storage expenses. In this study, we proposed a new method for reducing GNSS location data in both online and offline settings, utilizing an ANN trained with a mathematically generated dataset. ANN has not been used in data reduction in the literature. The approach involves training the ANN with a window size of 3 and a threshold value of 10°, followed by using the trained model for data reduction. Experimental results show that the ANN achieves a reduction rate of around 59.18% compared to the original trajectory. Notably, the ANN yields a significantly lower RMSE compared to a mathematical method, particularly in areas requiring precision. Despite the slightly slower computation times, the ANN remains suitable for real‐time applications, demonstrating its efficacy for GNSS location data reduction. Our study highlights its online capability, reasonable reduction rates, and low RMSE values, distinguishing it from existing literature. This method shows potential for scenarios where balancing reduction rates with data quality is crucial.

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Photo-realistic 3D model based accurate visual positioning system for large-scale indoor spaces

Cited by 3 publications

References 29 publications

Understanding Red Wine Quality with Feature Importance in Machine Learning and Explainable AI

Understanding Red Wine Quality with Feature Importance in Machine Learning and Explainable AI

Smartphone Photography Visual Localization Based on an Improved Siamese Neural Network

A New Approach to Reduce the Position Data of Moving Objects Using Neural Network

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