Landmark calibration for facial expressions and fish classification
Journal Publication ResearchOnline@JCUAbstract
This paper considers the automatic labeling of emotions in face images found on social media. Facial landmarks are commonly used to classify the emotions from a face image. However, it is difficult to accurately segment landmarks for some faces and for subtle emotions. Previous authors used a Gaussian prior for the refinement of landmarks, but their model often gets stuck in a local minima. Instead, the calibration of the landmarks with respect to the known emotion class label using principal component analysis is proposed in this paper. Next, the face image is generated from the landmarks using an image translation model. The proposed model is evaluated on the classification of facial expressions and also for fish identification underwater and outperforms baselines in accuracy by over 20%.
Journal
Signal, Image and Video Processing
Publication Name
N/A
Volume
16
ISBN/ISSN
1863-1711
Edition
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Issue
2
Pages Count
8
Location
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Publisher
Springer
Publisher Url
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Publisher Location
N/A
Publish Date
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Url
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Date
N/A
EISSN
N/A
DOI
10.1007/s11760-021-01943-0