A Survey on Applying Automated Recognition of Touchscreen Stroke Gestures to Children's Input. Issue 5 (21st April 2021)

• Record Type: Journal Article
• Authors: Shaw, Alex; Ruiz, Jaime; Anthony, Lisa
• Is Part Of: Interacting with computers. Volume 32:Issue 5-6(2020)
• Page Start: 524
• Page End: 547
• Publication Date: 2021-04-21
• Subjects: children -- drawing -- gesture -- learning -- recognition; Human-computer interaction -- Periodicals; 004.019
• DOI: 10.1093/iwc/iwab009
• Languages: English
• ISSNs: 0953-5438

Abstract

Abstract: Gesture recognition algorithms help designers create intelligent user interfaces for a number of application areas. However, these recognition algorithms are usually designed to recognize the gestures of adults, not children, and as such they generally do not perform as well for children as adults. Recognition of younger children's gestures is particularly poor when compared to recognition of older children's and adults' gestures. Researchers have begun to examine the aspects of children's gesture articulation patterns that make recognition difficult. This paper extends the initial work examining child-specific recognition approaches by considering general-purpose approaches and how they might apply to the problem of recognizing children's touchscreen gestures. This paper presents a survey of existing recognition and analysis techniques for gestures of both adults and children from a human-centered perspective, highlighting ways in which improved recognition can lead to a better experience for children using touchscreen gestures in a variety of contexts.