Abstract
This paper describes the smoke detection for autonomous vehicles using sensor fusion. The main difference from another algorithms is the ability to perform detection during ego movement. Laser data were used to shrink the region of interest suchwise decreasing processing time of the whole algorithm. Color and shape characteristics of smoke are used to detect possible smoke clouds which then refined by removing small objects and by filling holes. Sky region and lane markings are removed by checking edge density of the region. Other rigid objects are expelled by the boundary roughness feature. Finally, the shape descriptor was utilized to compare smoke regions in frame sequence to delete static objects.
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Filonenko, A., Hernández, D.C., Hoang, VD., Jo, KH. (2015). Smoke Detection for Autonomous Vehicles using Laser Range Finder and Camera. In: Ali, M., Kwon, Y., Lee, CH., Kim, J., Kim, Y. (eds) Current Approaches in Applied Artificial Intelligence. IEA/AIE 2015. Lecture Notes in Computer Science(), vol 9101. Springer, Cham. https://doi.org/10.1007/978-3-319-19066-2_58
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DOI: https://doi.org/10.1007/978-3-319-19066-2_58
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