Paper Info
Title
Device agnostic 3D gesture recognition using hidden Markov models
Abstract
Hidden Markov Models have been effectively used in pattern recognition systems in the past. In this work, we identify the necessary elements to successfully use an HMM system for 3D gesture recognition regardless of the sensor device being used. So long as the sensor system itself is capable of outputting information about the 3 axes of motion (X, Y, and Z), that information can be used in this generic model for accurate, high speed gesture recognition. The proposed system works with accelerometer data, positional data and gyro data alike.
Year
DOI
Venue
2009
10.1145/1639601.1639619
Future Play
Field
DocType
Citations 
Computer vision,Signature recognition,Gesture,Computer science,Accelerometer,Gesture recognition,Speech recognition,Sensor system,Artificial intelligence,Hidden Markov model
Conference
3
PageRank 
References 
Authors
0.43
2
2
Name
Order
Citations
PageRank
Anthony Whitehead114320.84
Kaitlyn Fox2184.55