Live demonstration: Real-time multi-hand segmentation on exhibition

Tsung Han Tsai, Shih An Huang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we proposed a multi-hand segmentation on exhibition. In exhibition there are many objects with similar color such as skin clothes and the decoration close to skin color. First we made a lot of virtual image to make the datasets closed to the exhibition, and combined the palm and back of hand into same picture. Secondly we proposed a robustness neural network call “Unet-Encoder Network (Unet-EN)” to train this datasets. We use pruning method to reduce the parameter and increase the speed. We implemented on NVIDIA® Jetson™ TX2. As a result, it can be implemented on some skin color space and supported multi-hand segmentation.

Original languageEnglish
Title of host publication2021 IEEE International Symposium on Circuits and Systems, ISCAS 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728192017
DOIs
StatePublished - 2021
Event53rd IEEE International Symposium on Circuits and Systems, ISCAS 2021 - Daegu, Korea, Republic of
Duration: 22 May 202128 May 2021

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
Volume2021-May
ISSN (Print)0271-4310

Conference

Conference53rd IEEE International Symposium on Circuits and Systems, ISCAS 2021
Country/TerritoryKorea, Republic of
CityDaegu
Period22/05/2128/05/21

Keywords

  • Hand segmentation
  • Skin color
  • TX2

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