TY - GEN
T1 - Pactolus
T2 - 34th Annual CHI Conference on Human Factors in Computing Systems, CHI EA 2016
AU - Chen, Yineng
AU - Su, Xiaojun
AU - Tian, Feng
AU - Huang, Jin
AU - Zhang, Xiaolong
AU - Dai, Guozhong
AU - Wang, Hongan
N1 - Funding Information:
This paper is based on work supported by the National Natural Science Foundation of China (Nos. 61232013, 61422212) and the National High Technology Research and Development Program (863 Program) of China (Nos. 2015AA020506, 2015AA016305).
Publisher Copyright:
© 2016 Authors.
PY - 2016/5/7
Y1 - 2016/5/7
N2 - Mid-air gestures have become an important interaction technique in natural user interfaces, especially in augmented reality and virtual reality. Supporting a set of continuous gesture-based commands in mid-air gesture interaction systems, such as selecting and moving then placing an object, however, remains to be a challenge. This is largely because these intentional command gestures are connected through transitional, meaningless gestures, which are often misleading for gesture recognition systems. The inability to separate unintentional movements from intentional command gestures, also called the Midas problem, limits the application of mid-air gestures. This paper addresses the Midas problem via a physiological computing approach. With the help of sensors that capture physiological signals, we present a novel method, Pactolus, for segmenting mid-air gestures using arm electromyography. User studies demonstrate the high accuracy of our approach in segmenting mid-air gestures interleaved by transitional hand or finger movements.
AB - Mid-air gestures have become an important interaction technique in natural user interfaces, especially in augmented reality and virtual reality. Supporting a set of continuous gesture-based commands in mid-air gesture interaction systems, such as selecting and moving then placing an object, however, remains to be a challenge. This is largely because these intentional command gestures are connected through transitional, meaningless gestures, which are often misleading for gesture recognition systems. The inability to separate unintentional movements from intentional command gestures, also called the Midas problem, limits the application of mid-air gestures. This paper addresses the Midas problem via a physiological computing approach. With the help of sensors that capture physiological signals, we present a novel method, Pactolus, for segmenting mid-air gestures using arm electromyography. User studies demonstrate the high accuracy of our approach in segmenting mid-air gestures interleaved by transitional hand or finger movements.
UR - https://www.scopus.com/pages/publications/85014660462
UR - https://www.scopus.com/inward/citedby.url?scp=85014660462&partnerID=8YFLogxK
U2 - 10.1145/2851581.2892492
DO - 10.1145/2851581.2892492
M3 - Conference contribution
AN - SCOPUS:85014660462
T3 - Conference on Human Factors in Computing Systems - Proceedings
SP - 1760
EP - 1765
BT - CHI EA 2016
PB - Association for Computing Machinery
Y2 - 7 May 2016 through 12 May 2016
ER -