Detail publikace

Acceleration of Server-side Image Processing by Client-side Pre-processing in Web Application Environment

JURÁNEK, L. ŠŤASTNÝ, J. ŠKORPIL, V. JUNEK, L.

Originální název

Acceleration of Server-side Image Processing by Client-side Pre-processing in Web Application Environment

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

The goal of this paper is to verify whether the use of client-side TensorFlow.js, a WebGL-accelerated JavaScript library for machine learning, can accelerate the processing of common photos by computer vision cloud services, such as detection and recognition of specific features like age, sex, expression or specific people in the image. This acceleration is based on pre-processing the input image, namely detecting human faces, which greatly changes the amount of input data that need to be uploaded to the cloud service and thus the amount of uploaded data compared to the original photograph. The upload speed of Internet connection often is, in the case of computer vision cloud services, the bottleneck of the whole system. That´s why decreasing the amount of uploaded data in time shorter than the difference between the total of upload and cloud service processing time of the original and the pre-processed image leads to acceleration.

Klíčová slova

cloud; face detection; image preprocessing; TenrFlow; WebGL

Autoři

JURÁNEK, L.; ŠŤASTNÝ, J.; ŠKORPIL, V.; JUNEK, L.

Vydáno

1. 7. 2019

Nakladatel

IEEE

Místo

Budapešť, Hungary

ISBN

978-1-7281-1864-2

Kniha

42nd International Conference on Telecommunications and Signal Processing (TSP 2019)

Strany od

127

Strany do

130

Strany počet

4

URL

BibTex

@inproceedings{BUT158145,
  author="Luboš {Juránek} and Jiří {Šťastný} and Vladislav {Škorpil} and Lukáš {Junek}",
  title="Acceleration of Server-side Image Processing by Client-side Pre-processing in Web Application Environment",
  booktitle="42nd International Conference on Telecommunications and Signal Processing (TSP 2019)",
  year="2019",
  pages="127--130",
  publisher="IEEE",
  address="Budapešť, Hungary",
  doi="10.1109/TSP.2019.8768889",
  isbn="978-1-7281-1864-2",
  url="https://ieeexplore.ieee.org/document/8769104"
}