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MUSeg: A multimodal semantic segmentation dataset for complex underground mine scenes.

Shiyan Li1, Qingqun Kong1, Xuan Gao1

  • 1School of Artificial Intelligence, China University of Mining and Technology-Beijing, Beijing, 100083, China.

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|July 8, 2025
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Summary
This summary is machine-generated.

This study introduces MUSeg, a new multimodal dataset for intelligent mining perception. It addresses challenges in underground mine visual perception, enabling advanced multimodal fusion semantic segmentation.

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Area of Science:

  • Computer Vision
  • Robotics
  • Geoscience Engineering

Background:

  • Underground mining faces challenges in visual perception due to harsh environments, limiting intelligent automation.
  • Visible light-based methods struggle in these conditions, necessitating multimodal approaches.
  • Existing multimodal datasets are insufficient for complex underground mine scenarios.

Purpose of the Study:

  • To develop and introduce the Multimodal Underground mine Semantic segmentation (MUSeg) dataset.
  • To provide a benchmark dataset for multimodal fusion semantic segmentation in underground mines.
  • To facilitate research and application of intelligent perception technologies in mining.

Main Methods:

  • Collected 3,171 aligned RGB and depth image pairs from six diverse Chinese mines.
  • Manually annotated 15 semantic object categories relevant to mine perception tasks.
  • Validated annotations with mining experts and evaluated the dataset with classical algorithms.

Main Results:

  • The MUSeg dataset offers a comprehensive resource for multimodal semantic segmentation in underground mines.
  • It addresses the critical lack of dedicated datasets in this specialized domain.
  • Initial evaluations demonstrate the dataset's utility for benchmarking algorithms.

Conclusions:

  • The MUSeg dataset is a significant contribution to intelligent mining, enabling advancements in perception.
  • It provides a foundation for developing and applying robust multimodal fusion algorithms.
  • This resource will accelerate the transition towards unmanned and intelligent mining operations.