Quantitative Modeling and Evaluation of Urban Landmark Building Image Impact Factor Based on Computer Big Data Framework

DOI

10.2991/978-94-6463-516-4_53How to use a DOI?

Keywords

City landmark; city image; particulate filtration; feature selection; target tracking

Abstract

This project innovates by intertwining urban identification with its context, seamlessly merging the urban identification system with natural, spatial, and historical dimensions. A distinctive urban logo system is constructed, reflecting urban characteristics. A landmark database and an attitude inference model are developed to refine robotic precision. During map generation, an amalgamation of visual and laser data produces a contextually rich laser image. Leveraging particle filtering, a novel online feature extraction technique is introduced, exploiting linear interdependencies among image components for segmentation. It selects the most discriminative sample for estimation based on calculated log-likelihood ratios, employing dual particle sets for target location approximation. Simulations confirm the method's superior tracking accuracy and robustness. The method involves harnessing two distinct methodologies to yield dual sets of particles aimed at approximating the target location. Simulation outcomes validate the superior tracking capabilities and resilience of this proposed approach.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Shengnan Zhang
AU  - Congna Lv
AU  - Yueming Yang
AU  - Yufei Zhang
PY  - 2024
DA  - 2024/09/17
TI  - Quantitative Modeling and Evaluation of Urban Landmark Building Image Impact Factor Based on Computer Big Data Framework
BT  - Proceedings of the 2024 5th International Conference on Urban Construction and Management Engineering (ICUCME 2024)
PB  - Atlantis Press
SP  - 500
EP  - 509
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-516-4_53
DO  - 10.2991/978-94-6463-516-4_53
ID  - Zhang2024
ER  -