Paper Info
Title
The Invisible Potential of Facial Electromyography - A Comparison of EMG and Computer Vision when Distinguishing Posed from Spontaneous Smiles.
Abstract
Positive experiences are a success metric in product and service design. Quantifying smiles is a method of assessing them continuously. Smiles are usually a cue of positive affect, but they can also be fabricated voluntarily. Automatic detection is a promising complement to human perception in terms of identifying the differences between smile types. Computer vision (CV) and facial distal electromyography (EMG) have been proven successful in this task. This is the first study to use a wearable EMG that does not obstruct the face to compare the performance of CV and EMG measurements in the task of distinguishing between posed and spontaneous smiles. The results showed that EMG has the advantage of being able to identify covert behavior not available through vision. Moreover, CV appears to be able to identify visible dynamic features that human judges cannot account for. This sheds light on the role of non-observable behavior in distinguishing affect-related smiles from polite positive affect displays.
Year
DOI
Venue
2019
10.1145/3290605.3300379
CHI
Keywords
Field
DocType
computer vision, electromyography, facial expression recognition
Service design,Facial electromyography,Computer vision,Facial expression recognition,Wearable computer,Computer science,Electromyography,Covert,Human–computer interaction,Artificial intelligence,Affect (psychology),Perception
Conference
ISBN
Citations 
PageRank 
978-1-4503-5970-2
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Monica Perusquía-Hernández133.10
Saho Ayabe-Kanamura200.68
Kenji Suzuki315038.54
Shiro Kumano414916.82