Dense Three-Dimensional Color Reconstruction for Large-Scale Outdoor Scenes | IEEE Conference Publication | IEEE Xplore

Dense Three-Dimensional Color Reconstruction for Large-Scale Outdoor Scenes


Abstract:

Accurate three-dimensional (3D) color models play a crucial role in various emerging applications, such as geographic surveying and mapping, smart cities, and digital twi...Show More

Abstract:

Accurate three-dimensional (3D) color models play a crucial role in various emerging applications, such as geographic surveying and mapping, smart cities, and digital twin cities. To achieve high-fidelity representations of large-scale scenes, recent advancements in machine learning techniques and LiDAR-based Simultaneous Localization and Mapping (SLAM) have been instrumental. Leveraging these cutting-edge technologies, this paper presents a sensor-fusion framework that integrates a solid-state LiDAR, an inertial measurement unit (IMU), and a monocular camera. Additionally, a point cloud upsampling technique is introduced into LiDAR SLAM to enhance the density of the point clouds. Within this framework, the LiDAR-IMU odometry accurately estimates the positions and poses of the collected point clouds. Simultaneously, synchronized images are captured and utilized to incorporate texture information into the point clouds. The proposed framework demonstrates its capability to generate highly detailed and dense 3D color models for large-scale outdoor scenes, all within a limited on-site scanning time. Extensive experimental results validate the effectiveness and efficiency of the proposed approach.
Date of Conference: 31 October 2023 - 03 November 2023
Date Added to IEEE Xplore: 20 November 2023
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Conference Location: Taipei, Taiwan

I. Introduction

Accurate reconstruction of large-scale outdoor scenes in three-dimensional (3D) color models is essential for various applications, including geographic surveying, urban planning, smart cities, digital twin cities, and environmental protection. However, outdoor scenes present unique challenges due to their complex and dynamic nature. One of the challenges arises from the sheer size and complexity of outdoor environments. These scenes often consist of numerous objects with diverse shapes and textures, making it difficult to capture and reconstruct them accurately. Moreover, outdoor scenes are subject to changing illumination conditions, which can affect the color and appearance of objects. Additionally, the presence of occlusions caused by trees, buildings, or other obstacles further complicates the reconstruction process.

References

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