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Railroad online: acquiring and visualizing route panoramas of rail scenes

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Abstract

A patrol type of surveillance has been performed everywhere from police city patrol to railway inspection. Different from static cameras or sensors distributed in a space, such surveillance has its benefits of low cost, long distance, and efficiency in detecting infrequent changes. However, the challenges are how to archive daily recorded videos in the limited storage space and how to build a visual representation for quick and convenient access to the archived videos. We tackle the problems by acquiring and visualizing route panoramas of rail scenes. We analyze the relation between train motion and the video sampling and the constraints such as resolution, motion blur and stationary blur etc. to obtain a desirable panoramic image. The route panorama generated is a continuous image with complete and non-redundant scene coverage and compact data size, which can be easily streamed over the network for fast access, maneuver, and automatic retrieval in railway environment monitoring. Then, we visualize the railway scene based on the route panorama rendering for interactive navigation, inspection, and scene indexing.

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Authors and Affiliations

  1. Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China

    Shengchun Wang, Siwei Luo & Yaping Huang

  2. Department of Computer and Information Science, Indiana University Purdue University Indianapolis, Indianapolis, USA

    Jiang Yu Zheng

  3. Infrastructure Inspection Research Institute, China Academy of Railway Sciences, Beijing, China

    Peng Dai & Qiang Han

Authors
  1. Shengchun Wang
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  2. Siwei Luo
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  3. Yaping Huang
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  4. Jiang Yu Zheng
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  5. Peng Dai
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  6. Qiang Han
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Corresponding author

Correspondence to Yaping Huang.

Additional information

This work is supported by National Nature Science Foundation of China (61272354, 61273364,61105119) and Fundamental Research Funds for the Central Universities (2012JBM039, 2011JBZ005).

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Wang, S., Luo, S., Huang, Y. et al. Railroad online: acquiring and visualizing route panoramas of rail scenes. Vis Comput 30, 1045–1057 (2014). https://doi.org/10.1007/s00371-013-0911-4

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  • DOI: https://doi.org/10.1007/s00371-013-0911-4

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