Detail výsledku
Feature extraction for efficient image and video segmentation
Beran Vítězslav, doc. Ing., Ph.D., UPGM (FIT)
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.
Color/Texture segmentation, Motion segmentation, RGB-D/T segmentation
@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/"
}