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An Efficient Deep Learning Framework for People Detection in Overhead Images

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Artificial Intelligence in Industrial Applications

Part of the book series: Learning and Analytics in Intelligent Systems ((LAIS,volume 25))

Abstract

People detection is an important issue in video surveillance applications. The factors such as severe occlusions and scene perspective distortions in real application scenarios complicate this task. This article proposes an efficient deep learning framework for detecting people from overhead images. The proposed method uses a multi-scale Yolov4-Tiny algorithm for person detection. The multi-scale feature of the algorithm enables it to successfully detect people who appear small in an image. A comparative analysis was made with non-maximum suppression (NMS) algorithms, which significantly affect the detection performance. In this context, it is aimed to determine the most suitable NMS algorithm for the multi-scale Yolov4-Tiny algorithm. The performance of this method has been evaluated by various experiments. The experiments were carried out on two datasets consisting of many difficulties such as light, distance, occlusion, and wear a hat. As a result of the experiments, 94.85% mean average precision (mAP) value was obtained with the proposed method. The proposed method not only shows promising results, but can also work in real-time applications due to low computational cost.

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Author information

Authors and Affiliations

  1. Özdilek Ev Tekstil San. Ve Tic. AŞ, Ozveri R&D Center, Bursa, Turkey

    Musa Peker, Bilge İnci, Elnura Musaoğlu, Hüseyin Çobanoğlu, Nadir Kocakır & Önder Karademir

Authors
  1. Musa Peker
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  2. Bilge İnci
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  3. Elnura Musaoğlu
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  4. Hüseyin Çobanoğlu
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  5. Nadir Kocakır
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  6. Önder Karademir
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Corresponding author

Correspondence to Musa Peker .

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Editors and Affiliations

  1. Department of Computer Science, Creighton University, Omaha, NE, USA

    Steven Lawrence Fernandes

  2. Shobhit University, Saharanpur, India

    Tarun K. Sharma

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Peker, M., İnci, B., Musaoğlu, E., Çobanoğlu, H., Kocakır, N., Karademir, Ö. (2022). An Efficient Deep Learning Framework for People Detection in Overhead Images. In: Fernandes, S.L., Sharma, T.K. (eds) Artificial Intelligence in Industrial Applications. Learning and Analytics in Intelligent Systems, vol 25. Springer, Cham. https://doi.org/10.1007/978-3-030-85383-9_1

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