Paper Info
Title
Multimodal identification using Markov logic networks
Abstract
Human robot interaction presents a unique set of challenges for biometric person identification. During normal interactions between the robot and a user, a tremendous amount of information is available for identification. Our objective is to use this information to identify users quickly and accurately during interactions with a robot. We present our approach for multimodal person identification using Markov logic networks (MLN). We use appearance, clothing, speaker recognition, and face recognition to identify a person during an interaction where they are speaking to the robot. We demonstrate the effectiveness of our approach using sequences of individuals speaking freely on a topic of their choosing.
Year
DOI
Venue
2011
10.1109/FG.2011.5771324
FG
Keywords
Field
DocType
speech,markov process,clothing,face,markov processes,human robot interaction,robots,face recognition,speaker recognition
Facial recognition system,Markov process,Markov chain,Clothing,Psychology,Speech recognition,Speaker recognition,Biometrics,Robot,Human–robot interaction
Conference
Citations 
PageRank 
References 
3
0.46
11
Authors
2
Name
Order
Citations
PageRank
Wallace E. Lawson1137.73
Eric Martinson212412.18