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A Comparative Study of Vehicle Detection Methods in a Video Sequence

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Book cover Distributed Computing for Emerging Smart Networks (DiCES-N 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1130))

Abstract

Vehicle detection plays a significant role in traffic monitoring. Vehicle detection approaches can be used for vehicle tracking, vehicle classification and traffic analysis. However, numerous attributes like shape, intensity, size, pose, illumination, shadows, occlusion, velocity of vehicles and environmental conditions, provide different challenges for the detection step. With an appropriate vehicle detection technique, we are able to extract valuable knowledge from video sequences, regardless these diverse factors. Since the vehicle detection method choice has a deep impact on this step and the whole traffic monitoring system performances, our objective in this study is to investigate different methods for vehicle detection. Comparison is made on the basis of different metrics such as recall, precision and detection accuracy. These approaches have been tested under different weather conditions (rainy, sunny) and various traffic conditions (light, medium, heavy).

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Acknowledgment

This work was financially supported by the PHC Utique program of the French Ministry of Foreign Affairs and Ministry of higher education and research and the Tunisian Ministry of higher education and scientific research in the CMCU project number 17G1417.

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Authors and Affiliations

  1. Faculty of sciences of Bizerte, University of Carthage, Tunis, Tunisia

    Ameni Chetouane, Sabra Mabrouk & Imen Jemili

  2. University of Bordeaux, Bordeaux, France

    Mohamed Mosbah

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  1. Ameni Chetouane
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  2. Sabra Mabrouk
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  3. Imen Jemili
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  4. Mohamed Mosbah
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Correspondence to Ameni Chetouane .

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Editors and Affiliations

  1. University of Carthage, Bizerte, Tunisia

    Imen Jemili

  2. Bordeaux INP, Talence, France

    Mohamed Mosbah

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Chetouane, A., Mabrouk, S., Jemili, I., Mosbah, M. (2020). A Comparative Study of Vehicle Detection Methods in a Video Sequence. In: Jemili, I., Mosbah, M. (eds) Distributed Computing for Emerging Smart Networks. DiCES-N 2019. Communications in Computer and Information Science, vol 1130. Springer, Cham. https://doi.org/10.1007/978-3-030-40131-3_3

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  • DOI: https://doi.org/10.1007/978-3-030-40131-3_3

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