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International Journal of Multimedia Information Retrieval

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30.10.2019 | Trends and Surveys

Single-image crowd counting: a comparative survey on deep learning-based approaches

verfasst von: Vy Nguyen, Thanh Duc Ngo

Erschienen in: International Journal of Multimedia Information Retrieval | Ausgabe 2/2020

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Abstract

Crowd counting is an attracting computer vision problem. Solutions to crowd counting hold high adaptability to other counting problems such as traffic counting and cell counting. Numerous methods have been proposed for the problem. Deep learning-based methods play a significant role in recent advancement. However, no existing literature reviews capture their sophisticated development by challenges. In this paper, we discuss and categorize recent deep learning works in crowd counting by considering how they address the challenges.

Vorheriger Artikel Special issue on deep learning in image and video retrieval

Nächster Artikel A study on deep learning spatiotemporal models and feature extraction techniques for video understanding

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Titel: Single-image crowd counting: a comparative survey on deep learning-based approaches
verfasst von: Vy Nguyen
Thanh Duc Ngo
Publikationsdatum: 30.10.2019
Verlag: Springer London
Erschienen in: International Journal of Multimedia Information Retrieval / Ausgabe 2/2020
Print ISSN: 2192-6611
Elektronische ISSN: 2192-662X
DOI: https://doi.org/10.1007/s13735-019-00181-y

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