Streamlined And Accurate Gesture Recognition With Penny Pincher

Keywords

$-family; Gesture recognition; Template matching

Abstract

Penny Pincher is a recently introduced template matching $-family gesture recognizer that exhibits competitive accuracy with even just one template. However, our recognizer is also able to rapidly compare a candidate gesture against numerous templates in a short amount of time, as compared to other recognizers, in order to achieve higher accuracy within a given time budget. Penny Pincher achieves this goal by reducing the template matching process to merely addition and multiplication; by avoiding translation, scaling, and rotation; and by avoiding calls to expensive geometric functions. In an evaluation compared against four other $-family recognizers, in three of our six datasets, Penny Pincher achieves the highest accuracy of all recognizers reaching 97.5%, 99.8%, and 99.9% user independent recognition accuracy, while remaining competitive with the three remaining datasets. Further, when a time constraint is imposed, our recognizer always exhibits the highest accuracy, realizing a reduction in recognition error of between 83% and 99% in most cases as Penny Pincher is able to process five times as many templates in the same amount of time as its closest competitor. Further, in this extended work, we also evaluate the effectiveness of Penny Pincher in a stressful setting using a video game prototype that makes heavy use of gestures, so that rushed and malformed gesture articulation is more likely. Our evaluation was conducted with a 24 participant between-subject user study of Protractor and Penny Pincher. Training data and in-game data collected during the user study was further used to evaluate several $-family recognizers. Again we find that our recognizer is on par with or better than the others, reducing the recognition error by as much as 5.8% to 10.4% with just a small number of templates per gesture.

Publication Date

4-1-2016

Publication Title

Computers and Graphics (Pergamon)

Volume

55

Number of Pages

130-142

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.cag.2015.10.011

Socpus ID

84960424662 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84960424662

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