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Saliency Detection in a Virtual Driving Environment for Autonomous Vehicle Behavior Improvement

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Augmented Reality, Virtual Reality, and Computer Graphics (AVR 2021)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12980))

Abstract

To make the best decisions in real-world situations, autonomous vehicles require learning algorithms that process a large number of labeled images. This paper aims to compare the automatically generated saliency maps with attention maps obtained with an eye-tracking device in order to provide automated labeling of images for the learning algorithm. To simulate traffic scenarios, we are using a virtual driving environment with a motion platform and an eye-tracking device for identifying the driver’s attention. The saliency maps are generated by post-processing the driver’s view provided by the front camera.

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Acknowledgement

This work was supported by a grant of the Ministry of Research, Innovation and Digitization, CNCS/CCCDI – UEFISCDI, project number PN-III-P2-2.1-PED-2019-4366 within PNCDI III (431PED).

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Authors and Affiliations

  1. Transilvania University of Brasov, 29 Eroilor, 500036, Brasov, Romania

    Csaba Antonya, Florin Gîrbacia, Cristian Postelnicu, Daniel Voinea & Silviu Butnariu

Authors
  1. Csaba Antonya
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  2. Florin Gîrbacia
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  3. Cristian Postelnicu
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  4. Daniel Voinea
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  5. Silviu Butnariu
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Corresponding author

Correspondence to Florin Gîrbacia .

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Editors and Affiliations

  1. University of Salento, Lecce, Italy

    Lucio Tommaso De Paolis

  2. University of Naples Federico II, Naples, Italy

    Pasquale Arpaia

  3. University of Paris-Sud, Orsay, France

    Patrick Bourdot

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Antonya, C., Gîrbacia, F., Postelnicu, C., Voinea, D., Butnariu, S. (2021). Saliency Detection in a Virtual Driving Environment for Autonomous Vehicle Behavior Improvement. In: De Paolis, L.T., Arpaia, P., Bourdot, P. (eds) Augmented Reality, Virtual Reality, and Computer Graphics. AVR 2021. Lecture Notes in Computer Science(), vol 12980. Springer, Cham. https://doi.org/10.1007/978-3-030-87595-4_37

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  • DOI: https://doi.org/10.1007/978-3-030-87595-4_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-87594-7

  • Online ISBN: 978-3-030-87595-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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