An adaptive eye gaze tracker system in the integrated cloud computing and mobile device

Chiao Wen Kao, Che Wei Yang, Kuo Chin Fan, Bor Jiunn Hwang, Chin Pan Huang

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

8 Scopus citations

Abstract

This paper proposed an adaptive method for tracking eye gaze in the integrated cloud computing and mobile device environment. The task begins with extracting the eye position and the iris contour base on geometrical features. These local gaze features are calculate and integrated to train a neural network. And the estimated gaze point is outputted from the trained NN (Neural Network) in the cloud computing. A utility function is proposed to decide the functionality is performed in the cloud or mobile device adaptively based on device and network conditions. Besides, our proposed method can improve system performance as well as overcome the problem for limited resource of mobile device.

Original languageEnglish
Title of host publicationProceedings of 2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011
Pages367-371
Number of pages5
DOIs
StatePublished - 2011
Event2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011 - Guilin, Guangxi, China
Duration: 10 Jul 201113 Jul 2011

Publication series

NameProceedings - International Conference on Machine Learning and Cybernetics
Volume1
ISSN (Print)2160-133X
ISSN (Electronic)2160-1348

Conference

Conference2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011
Country/TerritoryChina
CityGuilin, Guangxi
Period10/07/1113/07/11

Keywords

  • ANN
  • Cloud Computing
  • Eye Tracking
  • Mobile Device

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