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International Conference on Computer Vision Systems

ICVS 2017: Computer Vision Systems pp 195–204Cite as

A Computer Vision System to Localize and Classify Wastes on the Streets

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 10528)

Abstract

Littering quantification is an important step for improving cleanliness of cities. When human interpretation is too cumbersome or in some cases impossible, an objective index of cleanliness could reduce the littering by awareness actions. In this paper, we present a fully automated computer vision application for littering quantification based on images taken from the streets and sidewalks. We have employed a deep learning based framework to localize and classify different types of wastes. Since there was no waste dataset available, we built our acquisition system mounted on a vehicle. Collected images containing different types of wastes. These images are then annotated for training and benchmarking the developed system. Our results on real case scenarios show accurate detection of littering on variant backgrounds.

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Notes

  1. 1.

    http://www.cleaneuropenetwork.eu/de/measuring-litter/aus/.

  2. 2.

    http://www.avpu.fr/pdf%20AVPU/formation%20grille%20IOP-2014.pdf.

  3. 3.

    http://ec.europa.eu/regional_policy/sources/docgener/studies/pdf/urban/survey2015_en.pdf.

  4. 4.

    https://www.microsoft.com/cognitive-services/en-us/bing-image-search-api.

  5. 5.

    http://www.bafu.admin.ch/publikationen/publikation/01604/index.html?lang=fr.

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Acknowledgment

The authors would like to thank Mr. Niels Michel, Manager of Dialog & Service at City of Zurich for sharing his in-depth experience on cleanliness measurement thus significantly contributing to this project.

Author information

Authors and Affiliations

  1. Signal Processing Laboratory 5, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland

    Mohammad Saeed Rad & Jean-Philippe Thiran

  2. Cortexia SA, Chatel-Saint-Denis, Switzerland

    Andreas von Kaenel & Andre Droux

  3. Haute Ecole Arc, St-imier, Switzerland

    Francois Tieche & Nabil Ouerhani

  4. Istanbul Technical University, Istanbul, Turkey

    Hazım Kemal Ekenel

Authors
  1. Mohammad Saeed Rad
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  2. Andreas von Kaenel
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  3. Andre Droux
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  4. Francois Tieche
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  5. Nabil Ouerhani
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  6. Hazım Kemal Ekenel
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  7. Jean-Philippe Thiran
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Corresponding author

Correspondence to Mohammad Saeed Rad .

Editor information

Editors and Affiliations

  1. Hong Kong University of Science and Technology, Hong Kong, China

    Ming Liu

  2. Harbin Institute of Technology, Shenzhen, China

    Dr. Haoyao Chen

  3. Technische Universtiät Wien, Vienna, Austria

    Prof. Dr. Markus Vincze

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Rad, M.S. et al. (2017). A Computer Vision System to Localize and Classify Wastes on the Streets. In: Liu, M., Chen, H., Vincze, M. (eds) Computer Vision Systems. ICVS 2017. Lecture Notes in Computer Science(), vol 10528. Springer, Cham. https://doi.org/10.1007/978-3-319-68345-4_18

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  • DOI: https://doi.org/10.1007/978-3-319-68345-4_18

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