Paper Info
Title
Gesture Spotter: A Rapid Prototyping Tool for Key Gesture Spotting in Virtual and Augmented Reality Applications
Abstract
In this paper we examine the task of key gesture spotting: accurate and timely online recognition of hand gestures. We specifically seek to address two key challenges faced by developers when integrating key gesture spotting functionality into their applications. These are: i) achieving high accuracy and zero or negative activation lag with single-time activation; and ii) avoiding the requirement for deep domain expertise in machine learning. We address the first challenge by proposing a key gesture spotting architecture consisting of a novel gesture classifier model and a novel single-time activation algorithm. This key gesture spotting architecture was evaluated on four separate hand skeleton gesture datasets, and achieved high recognition accuracy with early detection. We address the second challenge by encapsulating different data processing and augmentation strategies, as well as the proposed key gesture spotting architecture, into a graphical user interface and an application programming interface. Two user studies demonstrate that developers are able to efficiently construct custom recognizers using both the graphical user interface and the application programming interface.
Year
DOI
Venue
2022
10.1109/TVCG.2022.3203004
IEEE Transactions on Visualization and Computer Graphics
Keywords
DocType
Volume
Gestures,Pattern Recognition, Automated,Augmented Reality,Computer Graphics,Algorithms,Hand
Journal
28
Issue
ISSN
Citations 
11
1077-2626
0
PageRank 
References 
Authors
0.34
25
4
Name
Order
Citations
PageRank
Junxiao Shen100.68
John J. Dudley2175.35
George Mo300.34
Per Ola Kristensson4131791.21