Publication detail

Centroid based person detection using pixelwise prediction of the position

DOLEŽEL, P. ŠKRABÁNEK, P. ŠTURSA, D. BARUQUE ZANON, B. COGOLLOS ADRIAN, H. KRÝDA, P.

Original Title

Centroid based person detection using pixelwise prediction of the position

Type

journal article in Web of Science

Language

English

Original Abstract

Implementations of person detection in tracking and counting systems tend towards processing of orthogonally captured images on edge computing devices. The ellipse-like shape of heads in orthogonally captured images inspired us to predict head centroids to determine positions of persons in images. We predict the centroids using a fully convolutional network (FCN). We combine the FCN with simple image processing operations to ensure fast inference of the detector. We experiment with the size of the FCN output to further decrease the inference time. We compare the proposed centroid-based detector with bounding box-based detectors on head detection task in terms of the inference time and the detection performance. We propose a performance measure which allows quantitative comparison of the two detection approaches. For the training and evaluation of the detectors, we form original datasets of 8000 annotated images, which are characterized by high variability in terms of lighting conditions, background, image quality, and elevation profile of scenes. We propose an approach which allows simultaneous annotation of the images for both bounding box-based and centroid-based detection. The centroid-based detector shows the best detection performance while keeping edge computing standards.

Keywords

Persondetection; Fullyconvolutionalnetworks; Performancemeasure; Edgecomputing; Computervision

Authors

DOLEŽEL, P.; ŠKRABÁNEK, P.; ŠTURSA, D.; BARUQUE ZANON, B.; COGOLLOS ADRIAN, H.; KRÝDA, P.

Released

6. 7. 2022

Publisher

ELSEVIER

Location

AMSTERDAM

ISBN

1877-7503

Periodical

Journal of Computational Science

Year of study

63

Number

1

State

Kingdom of the Netherlands

Pages from

1

Pages to

12

Pages count

12

URL

https://www.sciencedirect.com/science/article/pii/S1877750322001442

Full text in the Digital Library

http://hdl.handle.net/11012/208207

BibTex

@article{BUT178514,
  author="Petr {Doležel} and Pavel {Škrabánek} and Dominik {Štursa} and Bruno {Baruque Zanon} and Hector {Cogollos Adrian} and Pavel {Krýda}",
  title="Centroid based person detection using pixelwise prediction of the position",
  journal="Journal of Computational Science",
  year="2022",
  volume="63",
  number="1",
  pages="1--12",
  doi="10.1016/j.jocs.2022.101760",
  issn="1877-7503",
  url="https://www.sciencedirect.com/science/article/pii/S1877750322001442"
}