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Title: Towards the Synthesis of Parent-Infant Facial Interactions
This work is motivated by the need to automate the analysis of parent-infant interactions to better understand the existence of any potential behavioral patterns useful for the early diagnosis of autism spectrum disorder (ASD). It presents an approach for synthesizing the facial expression exchanges that occur during parent-infant interactions. This is accomplished by developing a novel approach that uses landmarks when synthesizing changing facial expressions. The proposed model consists of two components: (i) The first is a landmark converter that receives a set of facial landmarks and the target emotion as input and outputs a set of new landmarks transformed to match the emotion. (ii) The second component involves an image converter that takes in an input image, a target landmark and a target emotion and outputs a face transformed to match the input emotion. The inclusion of landmarks in the generation process proves useful in the generation of baby facial expressions; babies have somewhat different facial musculature and facial dynamics than adults. This paper presents a realistic-looking matrix of changing facial expressions sampled from a 2-D emotion continuum (valence and arousal) and displays successfully transferred facial expressions from real-life mother-infant dyads to novel ones.  more » « less
Award ID(s):
1846076
NSF-PAR ID:
10321197
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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