Publication detail

Hand Detection in Static Images, Video Sequences and Real Time Camera Feed

BRAVENEC, T.

Original Title

Hand Detection in Static Images, Video Sequences and Real Time Camera Feed

English Title

Hand Detection in Static Images, Video Sequences and Real Time Camera Feed

Type

conference paper

Language

en

Original Abstract

The goal of this project is to create a computer vision system capable of hand detection in static images and in video sequence either from existing recording or real time feed from connected camera. Algorithms commonly used for hand detection are mostly dependent on simple background and are very dependent on the lightning changes. To mostly eliminate these issues this project uses deep convolutional neural network trained for hand detection.

English abstract

The goal of this project is to create a computer vision system capable of hand detection in static images and in video sequence either from existing recording or real time feed from connected camera. Algorithms commonly used for hand detection are mostly dependent on simple background and are very dependent on the lightning changes. To mostly eliminate these issues this project uses deep convolutional neural network trained for hand detection.

Keywords

Computer Vision; Hand detection; Convolutional Neural Networks; Deep Learning

Released

25.04.2019

ISBN

978-80-214-5735-5

Book

Proceedings of the 25th Conference STUDENT EEICT 2019

Pages from

386

Pages to

389

Pages count

4

BibTex


@inproceedings{BUT159692,
  author="Tomáš {Bravenec}",
  title="Hand Detection in Static Images, Video Sequences and Real Time Camera Feed",
  annote="The goal of this project is to create a computer vision system capable of hand detection in static images and in video sequence either from existing recording or real time feed from connected camera. Algorithms commonly used for hand detection are mostly dependent on simple background and are very dependent on the lightning changes. To mostly eliminate these issues this project uses deep convolutional neural network trained for hand detection.",
  booktitle="Proceedings of the 25th Conference STUDENT EEICT 2019",
  chapter="159692",
  howpublished="online",
  year="2019",
  month="april",
  pages="386--389",
  type="conference paper"
}