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A Statistical Approach to Human-Like Visual Attention and Saliency Detection for Robot Vision: Application to Wildland Fires’ Detection

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Neural Networks and Artificial Intelligence (ICNNAI 2014)

Abstract

In this work we contribute to development of a real-time human-like intuitive artificial vision system taking advantage from visual attention skill. Implemented on a 6-wheels mobile robot equipped with communication facilities, such a system allows detecting combustion perimeter in real outdoor environment without prior knowledge. It opens appealing perspectives in fire-fighting strategy enhancement and in early-stage woodland fire’s detection. We provide experimental results showing as well the plausibility as the efficiency of the proposed system.

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Kachurka, V., Madani, K., Sabourin, C., Golovko, V. (2014). A Statistical Approach to Human-Like Visual Attention and Saliency Detection for Robot Vision: Application to Wildland Fires’ Detection. In: Golovko, V., Imada, A. (eds) Neural Networks and Artificial Intelligence. ICNNAI 2014. Communications in Computer and Information Science, vol 440. Springer, Cham. https://doi.org/10.1007/978-3-319-08201-1_12

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  • DOI: https://doi.org/10.1007/978-3-319-08201-1_12

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08200-4

  • Online ISBN: 978-3-319-08201-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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