Paper Info
Title
Estimating muscle activation patterns using a surrogate model of facial biomechanics.
Abstract
Analyzing the muscle activities that drive the expressive facial gestures can be a useful tool in assessing one's emotional state of mind. Since the skin motion is much easier to measure in comparison to the actual electrical excitation signal of facial muscles, a biomechanical model of the human face driven by these muscles can be a useful tool in relating the geometric information to the muscle activity. However, long computational time often hinders its practicality. The objective of this study was to replace the precise but computationally demanding biomechanical model by a much faster multivariate meta-model (surrogate model), such that a significant speedup (real-time interactive speed) can be achieved and data from the biomechanical model can be practically exploited. Using the proposed surrogate, muscle activation patterns of six key facial expressions were estimated in the iterative fit from the structured-light scanned geometric information.
Year
DOI
Venue
2013
10.1109/EMBC.2013.6611212
EMBC
Keywords
Field
DocType
biomechanics,expressive facial gestures,face recognition,muscle activities,emotional state of mind,facial biomechanics surrogate model,electrical excitation signal,multivariate metamodel,geometric information,gesture recognition,skin motion,muscle activation pattern estimation,human face,computational modeling,computer simulation,mathematical model,algorithms,data models,face
Computer vision,Facial recognition system,Computer science,Surrogate model,Gesture recognition,Electromyography,Facial expression,Facial muscles,Artificial intelligence,Speedup,Biomechanical Phenomena
Conference
Volume
ISSN
Citations 
2013
1557-170X
2
PageRank 
References 
Authors
0.40
4
4
Name
Order
Citations
PageRank
Tim Wu19014.11
Harald Martens220.40
Hunter P J31352177.64
Kumar Mithraratne4204.73