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FAR: Fourier Aerial Video Recognition

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Computer Vision – ECCV 2022 (ECCV 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13697))

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Abstract

We present an algorithm, Fourier Activity Recognition (FAR), for UAV video activity recognition. Our formulation uses a novel Fourier object disentanglement method to innately separate out the human agent (which is typically small) from the background. Our disentanglement technique operates in the frequency domain to characterize the extent of temporal change of spatial pixels, and exploits convolution-multiplication properties of Fourier transform to map this representation to the corresponding object-background entangled features obtained from the network. To encapsulate contextual information and long-range space-time dependencies, we present a novel Fourier Attention algorithm, which emulates the benefits of self-attention by modeling the weighted outer product in the frequency domain. Our Fourier attention formulation uses much fewer computations than self-attention. We have evaluated our approach on multiple UAV datasets including UAV Human RGB, UAV Human Night, Drone Action, and NEC Drone. We demonstrate a relative improvement of 8.02%–38.69% in top-1 accuracy and up to 3 times faster over prior works.

The second and third authors contributed equally.

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Acknowledgements

We thank Rohan Chandra for reviewing the paper. This research has been supported by ARO Grants W911NF1910069, W911NF2110026 and Army Cooperative Agreement W911NF2120076.

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Authors and Affiliations

  1. University of Maryland, College Park, USA

    Divya Kothandaraman, Tianrui Guan, Xijun Wang, Ming Lin & Dinesh Manocha

  2. DEVCOM Army Research Laboratory, Adelphi, USA

    Shuowen Hu

Authors
  1. Divya Kothandaraman
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  2. Tianrui Guan
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  3. Xijun Wang
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  4. Shuowen Hu
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  5. Ming Lin
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  6. Dinesh Manocha
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Correspondence to Divya Kothandaraman .

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Editors and Affiliations

  1. Tel Aviv University, Tel Aviv, Israel

    Shai Avidan

  2. University College London, London, UK

    Gabriel Brostow

  3. Google AI, Accra, Ghana

    Moustapha Cissé

  4. University of Catania, Catania, Italy

    Giovanni Maria Farinella

  5. Facebook (United States), Menlo Park, CA, USA

    Tal Hassner

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Kothandaraman, D., Guan, T., Wang, X., Hu, S., Lin, M., Manocha, D. (2022). FAR: Fourier Aerial Video Recognition. In: Avidan, S., Brostow, G., Cissé, M., Farinella, G.M., Hassner, T. (eds) Computer Vision – ECCV 2022. ECCV 2022. Lecture Notes in Computer Science, vol 13697. Springer, Cham. https://doi.org/10.1007/978-3-031-19836-6_37

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