Publication detail

Detection of Dogs in Video Using Statistical Classifiers

JURÁNEK, R.

Original Title

Detection of Dogs in Video Using Statistical Classifiers

Type

article in a collection out of WoS and Scopus

Language

English

Original Abstract

A common approach to pattern recognition and object detection is to use a statistical classifier. Widely used method is AdaBoost or its modifications which yields outstanding results in certain tasks like face detection. The aim of this work was to build real-time system for detection of dogs for surveillance purposes. The author of this paper thus explored the possibility that the AdaBoost based classifiers could be used for this task.

Keywords

Statistical classifier, WaldBoost, AdaBoost, Dog detection

Authors

JURÁNEK, R.

RIV year

2008

Released

12. 11. 2008

Publisher

Springer Verlag

Location

Heidelberg

ISBN

0302-9743

Periodical

Lecture Notes in Computer Science

State

Federal Republic of Germany

Pages from

1

Pages to

11

Pages count

11

URL

http://www.fit.vutbr.cz/research/groups/graph/publi/2008/2008-Juranek-ICCVG-DogDetection.pdf

BibTex

@inproceedings{BUT30730,
  author="Roman {Juránek}",
  title="Detection of Dogs in Video Using Statistical Classifiers",
  booktitle="Proceedings of International Conference on Computer Vision and Graphics 2008",
  year="2008",
  series="Lecture Notes in Computer Science",
  journal="Lecture Notes in Computer Science",
  pages="1--11",
  publisher="Springer Verlag",
  address="Heidelberg",
  issn="0302-9743",
  url="http://www.fit.vutbr.cz/research/groups/graph/publi/2008/2008-Juranek-ICCVG-DogDetection.pdf"
}