Detail publikace

On Possibilities of Human Head Detection for Person Flow Monitoring System

Dolezel P. Stursa D. Skrabanek P.

Originální název

On Possibilities of Human Head Detection for Person Flow Monitoring System

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

Along with the development of human society, economy, industry and engineering, as well as with growing population in the world’s biggest cities, various approaches to person detection have become the subject of great interest. One approach to developing a person detection system is proposed in this paper. A high-angle video sequence is considered as the input to the system. Then, three classification algorithms are considered: support vector machines, pattern recognition neural networks and convolutional neural networks. The results showed very little difference between the classifiers, with the overall accuracy more than 95% over a testing set.

Klíčová slova

Person flow monitoring, Support vector machines, Pattern recognition neural network, Convolutional neural network. Histograms of oriented gradients

Autoři

Dolezel P.; Stursa D.; Skrabanek P.

Vydáno

16. 5. 2019

Nakladatel

Springer Verlag

Místo

Cham

ISSN

0302-9743

Periodikum

Lecture Notes in Computer Science

Ročník

11507 LNCS

Stát

Spolková republika Německo

Strany od

402

Strany do

413

Strany počet

12

URL

https://link.springer.com/chapter/10.1007/978-3-030-20518-8_34

BibTex

@inproceedings{BUT157763,
  author="Dolezel P. and Stursa D. and Skrabanek P.",
  title="On Possibilities of Human Head Detection for Person Flow Monitoring System",
  booktitle="Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
  year="2019",
  journal="Lecture Notes in Computer Science",
  volume="11507 LNCS",
  pages="402--413",
  publisher="Springer Verlag",
  address="Cham",
  doi="10.1007/978-3-030-20518-8\{_}34",
  issn="0302-9743",
  url="https://link.springer.com/chapter/10.1007/978-3-030-20518-8_34"
}