A robust tracking algorithm for 3D hand gesture with rapid hand motion through deep learning

Sanchez Riera Jordi, Yuan Sheng Hsiao, Tekoing Lim, Kai Lung Hua, Wen-Huang Cheng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Scopus citations

Abstract

There are two main problems that make hand gesture tracking especially difficult. One is the great number of degrees of freedom of the hand and the other one is the rapid movements that we make in natural gestures. Algorithms based on minimizing an objective function, with a good initialization, typically obtain good accuracy at low frame rates. However, these methods are very dependent on the initialization point, and fast movements on the hand position or gesture, provokes a lost of track which are unable to recover. We present a method that uses deep learning to train a set of gestures (81 gestures), that will be used as a rough estimate of the hand pose and orientation. This will serve to a registration of non rigid model algorithm that will find the parameters of hand, even when temporal assumption of smooth movements of hands is violated. To evaluate our proposed algorithm, different experiments are performed with some real sequences recorded with Intel depth sensor to demonstrate the performance in a real scenario.

Original languageEnglish
Title of host publication2014 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479947171
DOIs
StatePublished - 3 Sep 2014
Event2014 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2014 - Chengdu, China
Duration: 14 Jul 201418 Jul 2014

Publication series

Name2014 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2014

Conference

Conference2014 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2014
CountryChina
CityChengdu
Period14/07/1418/07/14

Keywords

  • Deep Learning
  • Gesture Recognition
  • Hand Model
  • Optimization
  • Tracking

Fingerprint Dive into the research topics of 'A robust tracking algorithm for 3D hand gesture with rapid hand motion through deep learning'. Together they form a unique fingerprint.

  • Cite this

    Jordi, S. R., Hsiao, Y. S., Lim, T., Hua, K. L., & Cheng, W-H. (2014). A robust tracking algorithm for 3D hand gesture with rapid hand motion through deep learning. In 2014 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2014 [6890556] (2014 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICMEW.2014.6890556