Attentive gesture recognition

Samuel F. Dodge, Lina Karam

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

2 Scopus citations


This paper presents a novel method for static gesture recognition based on visual attention. Our proposed method makes use of a visual attention model to automatically select points that correspond to fixation points of the human eye. Gesture recognition is then performed using the determined visual attention fixation points. For this purpose, shape context descriptors are used to compare the sparse fixation points of gestures for classification. Simulation results are presented in order to illustrate the performance of the proposed perceptual-based attentive gesture recognition method. The proposed method not only helps in the development of more natural user-centric interactive interfaces but is also able to achieve a 96.42% classification accuracy on the Triesch database of hand postures, which is superior to other methods presented in the literature.

Original languageEnglish (US)
Title of host publication2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings
Number of pages4
StatePublished - Dec 1 2012
Event2012 19th IEEE International Conference on Image Processing, ICIP 2012 - Lake Buena Vista, FL, United States
Duration: Sep 30 2012Oct 3 2012

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880


Other2012 19th IEEE International Conference on Image Processing, ICIP 2012
Country/TerritoryUnited States
CityLake Buena Vista, FL


  • Static gesture recognition
  • human computer interaction
  • visual attention

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems


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