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A framework for computing asset-sighting distance
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DOI：10.1007/s10044-012-0268-8.png)
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摘要
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Safety critical railway assets need to be visible from prescribed distances, ensuring safety. Traditional methods for measuring these sighting distances involve manual labour and disruption of rail services. Drawing parallels with other areas, efficiency and cost of such a task can be improved with automation. Hence, in this work, we describe a framework providing such automation, using image frames captured from video equipment as input. Any such framework needs to meet a set of associated challenges, including: determining the image position of decreasing sized assets as they appear farther from the observer, extracting three-dimensional positioning information (relative to motion) from two-dimensional video information and determining when an asset can no longer be seen (i.e. the sighting distance). Results show that the methods included in this framework perform better than a traditional method and information regarding asset-sighting distance is accurately computed.
Keyword:
Sighting distance
Object tracking
Ego-motion
Three-dimensional pose recovery
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