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Comparison of video-based pointing and selection techniques for hands-free text entry

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


Original languageEnglish
Title of host publicationProceedings of the Working Conference on Advanced Visual Interfaces, AVI 2012
Number of pages8
Publication statusPublished - 2012
Publication typeA4 Article in a conference publication
Event2012 International Working Conference on Advanced Visual Interfaces, AVI 2012 - Capri Island, Italy
Duration: 21 May 201225 May 2012


Conference2012 International Working Conference on Advanced Visual Interfaces, AVI 2012
CityCapri Island


Video-based human-computer interaction has received increasing interest over the years. However, earlier research has been mainly focusing on technical characteristics of different methods rather than on user performance and experiences in using computer vision technology. This study aims to investigate performance characteristics of novice users and their subjective experiences in typing text with several video-based pointing and selection techniques. In Experiment 1, eye tracking and head tracking were applied for the task of pointing at the keys of a virtual keyboard. The results showed that gaze pointing was significantly faster but also more erroneous technique as compared with head pointing. Self-reported subjective ratings revealed that it was generally better, faster, more pleasant and efficient to type using gaze pointing than head pointing. In Experiment 2, mouth open and brows up facial gestures were utilized for confirming the selection of a given character. The results showed that text entry speed was approximately the same for both selection techniques, while mouth interaction caused significantly fewer errors than brow interaction. Subjective ratings did not reveal any significant differences between the techniques. Possibilities for design improvements are discussed.

ASJC Scopus subject areas


  • computer vision, eye tracking, face detection, text entry, video-based interaction, virtual keyboard, visual gesture