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Temporal Extension for Encoder-Decoder-based Crowd Counting Approaches

: Golda, Thomas; Krüger, Florian; Beyerer, Jürgen

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MVA Organization; International Association for Pattern Recognition -IAPR-:
17th International Conference on Machine Vision Applications, MVA 2021. Online Proceedings. Online resource : July 25-27, 2021, Fully online, Japan
Online im WWW, 2021
Paper P2-1, 5 S.
International Conference on Machine Vision Applications (MVA) <17, 2021, Online>
Bundesministerium für Bildung und Forschung BMBF (Deutschland)
13N15164; ESCAPE
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IOSB ()

Crowd counting is an important aspect to safety monitoring at mass events and can be used to initiate safety measures in time. State-of-the-art encoder decoder architectures are able to estimate the number of people in a scene precisely. However, since most of the proposed methods are based to solely operate on single-image features, we observe that estimated counts for aerial video sequences are inherently noisy, which in turn reduces the significance of the overall estimates. In this paper, we propose a simple temporal extension to said encoder-decoder architectures that incorporates local context from multiple frames into the estimation process. By applying the temporal extension a state-of-the-art architectures and exploring multiple configuration settings, we find that the resulting estimates are more precise and smoother over time.