Paper Info
Title
Classification of holding hand for dynamic interface adjustment on mobile devices
Abstract
This work proposes a gesture-based left and right hand recognition algorithm for dynamic interface adjustment by using the information of the accelerometer and the touch screen on a mobile device. We design a warping method that aligns accelerometer signals with their corresponding positions of unlock-screen gestures. By projecting samples onto feature space and using a support vector machine classifier, the proposed method yields high recognition accuracy. The experiments also show that the proposed method is able to make correct decisions for a new user without pre-gathering information from the user.
Year
DOI
Venue
2014
10.1109/GCCE.2014.7031162
GCCE
Keywords
Field
DocType
accelerometers,gesture recognition,image classification,support vector machines,touch sensitive screens,accelerometer,dynamic interface adjustment,gesture-based left hand recognition algorithm,gesture-based right hand recognition algorithm,holding hand classification,mobile device,recognition accuracy,support vector machine classifier,touch screen,warping method,gesture,layout,accuracy
Computer vision,Feature vector,Image warping,Gesture,Computer science,Accelerometer,Support vector machine,Gesture recognition,Speech recognition,Mobile device,Artificial intelligence,Recognition algorithm
Conference
Citations 
PageRank 
References 
0
0.34
3
Authors
3
Name
Order
Citations
PageRank
Shih-Han Hsu100.34
Hsu-Yung Cheng224323.56
Chih-Chang Yu300.34