Publication detail

Feature extraction for efficient image and video segmentation

VOJVODA, J. BERAN, V.

Original Title

Feature extraction for efficient image and video segmentation

Type

conference paper

Language

English

Original Abstract

The segmentation of sensory data of various domains is often crucial pre-processing step in many computer vision methods and applications. In this work, we propose a method that leverages the quantization of local features distributions for the depth and the temporal information. Three variants of the segmentation method is designed and evaluated reflecting various data domains: space (color and texture), temporal (motion) and depth domain. Each variant was tested on appropriate dataset showing the usability of designed method for applications like areal-image analysis, hand detection and moving-people detection. The pilot experiments shows the characteristics of the approach and computational costs of designed variants. 

Keywords

Color/Texture segmentation, Motion segmentation, RGB-D/T segmentation

Authors

VOJVODA, J.; BERAN, V.

Released

27. 4. 2016

Publisher

Association for Computing Machinery

Location

Smolenice

ISBN

978-1-4503-4436-4

Book

Proceedings - SCCG 2016: 32nd Spring Conference on Computer Graphics

Pages from

75

Pages to

80

Pages count

6

URL

https://www.fit.vut.cz/research/publication/11086/

BibTex

@inproceedings{BUT130940,
  author="Jakub {Vojvoda} and Vítězslav {Beran}",
  title="Feature extraction for efficient image and video segmentation",
  booktitle="Proceedings - SCCG 2016: 32nd Spring Conference on Computer Graphics",
  year="2016",
  pages="75--80",
  publisher="Association for Computing Machinery",
  address="Smolenice",
  doi="10.1145/2948628.2948631",
  isbn="978-1-4503-4436-4",
  url="https://www.fit.vut.cz/research/publication/11086/"
}